Selected Publications

Categorised by year , by venue . Full publication list . Full list in PDF .

Google scholar (71271 citations) , DBLP , arXiv .

Journal: 67

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI): 42

International Journal of Computer Vision (IJCV): 25

End-to-end video text spotting with Transformer
\(\cdot\) W. Wu, C. Shen, Y. Cai, D. Zhang, Y. Fu, P. Luo, H. Zhou.
\(\cdot\) International Journal of Computer Vision (IJCV), 2024.
\(\cdot\) bibtex google scholar semantic scholar
Towards robust monocular depth estimation: a new baseline and benchmark
\(\cdot\) K. Xian, Z. Cao, C. Shen, G. Lin.
\(\cdot\) International Journal of Computer Vision (IJCV), 2024.
\(\cdot\) bibtex google scholar semantic scholar
Scaling up multi-domain semantic segmentation with sentence embeddings
\(\cdot\) W. Yin, Y. Liu, C. Shen, B. Sun, A. van den Hengel.
\(\cdot\) International Journal of Computer Vision (IJCV), 2024.
\(\cdot\) bibtex google scholar semantic scholar
Super vision transformer
\(\cdot\) M. Lin, M. Chen, Y. Zhang, C. Shen, R. Ji, L. Cao.
\(\cdot\) International Journal of Computer Vision (IJCV), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
A dynamic feature interaction framework for multi-task visual perception
\(\cdot\) Y. Xi, H. Chen, N. Wang, P. Wang, Y. Zhang, C. Shen, Y. Liu.
\(\cdot\) International Journal of Computer Vision (IJCV), 2023.
\(\cdot\) bibtex google scholar semantic scholar
From open set to closed set: supervised spatial divide-and-conquer for object counting
\(\cdot\) H. Xiong, H. Lu, C. Liu, L. Liu, C. Shen, Z. Cao.
\(\cdot\) International Journal of Computer Vision (IJCV), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar
SPL-Net: spatial-semantic patch learning network for facial attribute recognition with limited labeled data
\(\cdot\) Y. Yan, Y. Shu, S. Chen, J. Xue, C. Shen, H. Wang.
\(\cdot\) International Journal of Computer Vision (IJCV), 2023.
\(\cdot\) bibtex google scholar semantic scholar
SegViT v2: exploring efficient and continual semantic segmentation with plain vision transformers
\(\cdot\) B. Zhang, L. Liu, M. Phan, Z. Tian, C. Shen, Y. Liu.
\(\cdot\) International Journal of Computer Vision (IJCV), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Structured binary neural networks for image recognition
\(\cdot\) B. Zhuang, C. Shen, M. Tan, P. Chen, L. Liu, I. Reid.
\(\cdot\) International Journal of Computer Vision (IJCV), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Unsupervised scale-consistent depth learning from video
\(\cdot\) J. Bian, H. Zhan, N. Wang, Z. Li, L. Zhang, C. Shen, M. Cheng, I. Reid.
\(\cdot\) International Journal of Computer Vision (IJCV), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Joint classification and regression for visual tracking with fully convolutional Siamese networks
\(\cdot\) Y. Cui, D. Guo, Y. Shao, Z. Wang, C. Shen, L. Zhang, S. Chen.
\(\cdot\) International Journal of Computer Vision (IJCV), 2021.
\(\cdot\) bibtex google scholar semantic scholar
Exploring the capacity of an orderless box discretization network for multi-orientation scene text detection
\(\cdot\) Y. Liu, T. He, H. Chen, X. Wang, C. Luo, S. Zhang, C. Shen, L. Jin.
\(\cdot\) International Journal of Computer Vision (IJCV), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
NAS-FCOS: efficient search for object detection architectures
\(\cdot\) N. Wang, Y. Gao, H. Chen, P. Wang, Z. Tian, C. Shen, Y. Zhang.
\(\cdot\) International Journal of Computer Vision (IJCV), 2021.
\(\cdot\) bibtex google scholar semantic scholar project webpage
A dual-attention-guided network for ghost-free high dynamic range imaging
\(\cdot\) Q. Yan, D. Gong, Q. Shi, A. van den Hengel, C. Shen, I. Reid, Y. Zhang.
\(\cdot\) International Journal of Computer Vision (IJCV), 2021.
\(\cdot\) bibtex google scholar semantic scholar project webpage
BiSeNet v2: bilateral network with guided aggregation for real-time semantic segmentation
\(\cdot\) C. Yu, C. Gao, J. Wang, G. Yu, C. Shen, N. Sang.
\(\cdot\) International Journal of Computer Vision (IJCV), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Memory-efficient hierarchical neural architecture search for image restoration
\(\cdot\) H. Zhang, Y. Li, H. Chen, C. Gong, Z. Bai, C. Shen.
\(\cdot\) International Journal of Computer Vision (IJCV), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Separating content from style using adversarial learning for recognizing text in the wild
\(\cdot\) C. Luo, Q. Lin, Y. Liu, L. Jin, C. Shen.
\(\cdot\) International Journal of Computer Vision (IJCV), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Adaptive importance learning for improving lightweight image super-resolution network
\(\cdot\) L. Zhang, P. Wang, C. Shen, L. Liu, W. Wei, Y. Zhang, A. van den Hengel.
\(\cdot\) International Journal of Computer Vision (IJCV), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Cluster sparsity field: an internal hyperspectral imagery prior for reconstruction
\(\cdot\) L. Zhang, W. Wei, Y. Zhang, C. Shen, A. van den Hengel, Q. Shi.
\(\cdot\) International Journal of Computer Vision (IJCV), 2018.
\(\cdot\) pdf bibtex google scholar semantic scholar
Structured learning of binary codes with column generation for optimizing ranking measures
\(\cdot\) G. Lin, F. Liu, C. Shen, J. Wu, H. Shen.
\(\cdot\) International Journal of Computer Vision (IJCV), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Mining mid-level visual patterns with deep CNN activations
\(\cdot\) Y. Li, L. Liu, C. Shen, A. van den Hengel.
\(\cdot\) International Journal of Computer Vision (IJCV), 2016.
\(\cdot\) arXiv link bibtex google scholar semantic scholar project webpage
Efficient semidefinite branch-and-cut for MAP-MRF inference
\(\cdot\) P. Wang, C. Shen, A. van den Hengel, P. Torr.
\(\cdot\) International Journal of Computer Vision (IJCV), 2016.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
Unsupervised feature learning for dense correspondences across scenes
\(\cdot\) C. Zhang, C. Shen, T. Shen.
\(\cdot\) International Journal of Computer Vision (IJCV), 2016.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Extrinsic methods for coding and dictionary learning on Grassmann manifolds
\(\cdot\) M. Harandi, R. Hartley, C. Shen, B. Lovell, C. Sanderson.
\(\cdot\) International Journal of Computer Vision (IJCV), 2015.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Training effective node classifiers for cascade classification
\(\cdot\) C. Shen, P. Wang, S. Paisitkriangkrai, A. van den Hengel.
\(\cdot\) International Journal of Computer Vision (IJCV), 2013.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
Self-supervised 3d scene flow estimation and motion prediction using local rigidity prior
\(\cdot\) R. Li, C. Zhang, Z. Wang, C. Shen, G. Lin.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Single-path bit sharing for automatic loss-aware model compression
\(\cdot\) J. Liu, B. Zhuang, P. Chen, C. Shen, J. Cai, M. Tan.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar
SPTS v2: single-point scene text spotting
\(\cdot\) Y. Liu, J. Zhang, D. Peng, M. Huang, X. Wang, J. Tang, C. Huang, D. Lin, C. Shen, X. Bai, L. Jin.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
SC-DepthV3: robust self-supervised monocular depth estimation for dynamic scenes
\(\cdot\) L. Sun, J. Bian, H. Zhan, W. Yin, I. Reid, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Learning from partially labeled data for multi-organ and tumor segmentation
\(\cdot\) Y. Xie, J. Zhang, Y. Xia, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Dynamic convolution for 3D point cloud instance segmentation
\(\cdot\) T. He, C. Shen, A. van den Hengel.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar
FCOS: a simple and strong anchor-free object detector
\(\cdot\) Z. Tian, C. Shen, H. Chen, T. He.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
\(\cdot\) link bibtex google scholar semantic scholar project webpage
Instance and panoptic segmentation using conditional convolutions
\(\cdot\) Z. Tian, B. Zhang, H. Chen, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Towards accurate reconstruction of 3D scene shape from a single monocular image
\(\cdot\) W. Yin, J. Zhang, O. Wang, S. Niklaus, S. Chen, Y. Liu, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
DeepEMD: differentiable earth mover's distance for few-shot learning
\(\cdot\) C. Zhang, Y. Cai, G. Lin, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Auto-rectify network for unsupervised indoor depth estimation
\(\cdot\) J. Bian, H. Zhan, N. Wang, T. Chin, C. Shen, I. Reid.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
\(\cdot\) bibtex google scholar semantic scholar
ABCNet v2: adaptive bezier-curve network for real-time end-to-end text spotting
\(\cdot\) Y. Liu, C. Shen, L. Jin, T. He, P. Chen, C. Liu, H. Chen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Towards end-to-end text spotting in natural scenes
\(\cdot\) P. Wang, H. Li, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
PAN++: towards efficient and accurate end-to-end spotting of arbitrarily-shaped text
\(\cdot\) W. Wang, E. Xie, X. Li, X. Liu, D. Liang, Z. Yang, T. Lu, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
SOLO: a simple framework for instance segmentation
\(\cdot\) X. Wang, R. Zhang, C. Shen, T. Kong, L. Li.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Virtual normal: enforcing geometric constraints for accurate and robust depth prediction
\(\cdot\) W. Yin, Y. Liu, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Effective training of convolutional neural networks with low-bitwidth weights and activations
\(\cdot\) B. Zhuang, J. Liu, M. Tan, L. Liu, I. Reid, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Improving generative adversarial networks with local coordinate coding
\(\cdot\) J. Cao, Y. Guo, Q. Wu, C. Shen, J. Huang, M. Tan.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Adversarial learning of structure-aware fully convolutional networks for landmark localization
\(\cdot\) Y. Chen, C. Shen, H. Chen, X. Wei, L. Liu, J. Yang.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
Structured knowledge distillation for dense prediction
\(\cdot\) Y. Liu, C. Shun, J. Wang, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
\(\cdot\) arXiv link bibtex google scholar semantic scholar project webpage
Index networks
\(\cdot\) H. Lu, Y. Dai, C. Shen, S. Xu.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
\(\cdot\) arXiv link bibtex google scholar semantic scholar project webpage
Ordered or orderless: a revisit for video based person re-identification
\(\cdot\) L. Zhang, Z. Shi, J. Zhou, M. Cheng, Y. Liu, J. Bian, Z. Zeng, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
\(\cdot\) arXiv link bibtex google scholar semantic scholar project webpage
Plenty is plague: fine-grained learning for visual question answering
\(\cdot\) Y. Zhou, R. Ji, J. Su, X. Sun, D. Meng, Y. Gao, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
\(\cdot\) link bibtex google scholar semantic scholar
RefineNet: multi-path refinement networks for dense prediction
\(\cdot\) G. Lin, F. Liu, A. Milan, C. Shen, I. Reid.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019.
\(\cdot\) link bibtex google scholar semantic scholar project webpage
1. Pytorch code is here.
Ordinal constraint binary coding for approximate nearest neighbor search
\(\cdot\) H. Liu, R. Ji, J. Wang, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.
\(\cdot\) pdf bibtex google scholar semantic scholar
FVQA: fact-based visual question answering
\(\cdot\) P. Wang, Q. Wu, C. Shen, A. Dick, A. van den Hengel.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Exploring context with deep structured models for semantic segmentation
\(\cdot\) G. Lin, C. Shen, A. van den Hengel, I. Reid.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Cross-convolutional-layer pooling for image recognition
\(\cdot\) L. Liu, C. Shen, A. van den Hengel.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
Compositional model based Fisher vector coding for image classification
\(\cdot\) L. Liu, P. Wang, C. Shen, L. Wang, A. van den Hengel, C. Wang, H. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Image captioning and visual question answering based on attributes and external knowledge
\(\cdot\) Q. Wu, C. Shen, P. Wang, A. Dick, A. van den Hengel.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Online metric-weighted linear representations for robust visual tracking
\(\cdot\) X. Li, C. Shen, A. Dick, Z. Zhang, Y. Zhuang.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Learning depth from single monocular images using deep convolutional neural fields
\(\cdot\) F. Liu, C. Shen, G. Lin, I. Reid.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
\(\cdot\) arXiv link bibtex google scholar semantic scholar project webpage
A generalized probabilistic framework for compact codebook creation
\(\cdot\) L. Liu, L. Wang, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
Pedestrian detection with spatially pooled features and structured ensemble learning
\(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
\(\cdot\) arXiv link bibtex google scholar semantic scholar project webpage
Large-scale binary quadratic optimization using semidefinite relaxation and applications
\(\cdot\) P. Wang, C. Shen, A. van den Hengel, P. Torr.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
Supervised hashing using graph cuts and boosted decision trees
\(\cdot\) G. Lin, C. Shen, A. van den Hengel.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2015.
\(\cdot\) arXiv link bibtex google scholar semantic scholar project webpage
StructBoost: Boosting methods for predicting structured output variables
\(\cdot\) C. Shen, G. Lin, A. van den Hengel.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014.
\(\cdot\) arXiv link pdf bibtex google scholar semantic scholar
A hierarchical word-merging algorithm with class separability measure
\(\cdot\) L. Wang, L. Zhou, C. Shen, L. Liu, H. Liu.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014.
\(\cdot\) pdf bibtex google scholar semantic scholar
Incremental learning of 3D-DCT compact representations for robust visual tracking
\(\cdot\) X. Li, A. Dick, C. Shen, A. van den Hengel, H. Wang.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2013.
\(\cdot\) arXiv link pdf bibtex google scholar semantic scholar project webpage
UBoost: Boosting with the Universum
\(\cdot\) C. Shen, P. Wang, F. Shen, H. Wang.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2012.
\(\cdot\) pdf bibtex google scholar semantic scholar
On the dual formulation of boosting algorithms
\(\cdot\) C. Shen, H. Li.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2010.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
Adaptive object tracking based on an effective appearance filter
\(\cdot\) H. Wang, D. Suter, K. Schindler, C. Shen.
\(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2007.
\(\cdot\) link pdf bibtex google scholar semantic scholar
1. Featured article of September issue 2007.

Conference: 180

Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR): 93

Proc. IEEE International Conference on Computer Vision (ICCV): 34

Proc. European Conference on Computer Vision (ECCV): 24

Proc. International Conference on Machine Learning (ICML): 6

Proc. International Conference on Learning Represenations (ICLR): 4

Proc. Advances in Neural Information Processing Systems (NeurIPS): 19

FreeCustom: tuning-free customized image generation for multi-concept composition
\(\cdot\) G. Ding, C. Zhao, W. Wang, Z. Yang, Z. Liu, H. Chen, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’24), 2024.
\(\cdot\) bibtex google scholar semantic scholar
DiverGen: improving instance segmentation by learning wider data distribution with more diverse generative data
\(\cdot\) C. Fan, M. Zhu, H. Chen, Y. Liu, W. Wu, H. Zhang, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’24), 2024.
\(\cdot\) bibtex google scholar semantic scholar
Traffic scene parsing through the tsp6k dataset
\(\cdot\) P. Jiang, Y. Yang, Y. Cao, Q. Hou, M. Cheng, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’24), 2024.
\(\cdot\) bibtex google scholar semantic scholar
Learning conditional attributes for compositional zero-shot learning
\(\cdot\) Q. Wang, L. Liu, C. Jing, H. Chen, G. Liang, P. Wang, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’23), 2023.
\(\cdot\) bibtex google scholar semantic scholar
Images speak in images: a generalist painter for in-context visual learning
\(\cdot\) X. Wang, W. Wang, Y. Cao, C. Shen, T. Huang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’23), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Boosting robustness of image matting with context assembling and strong data augmentation
\(\cdot\) Y. Dai, B. Price, H. Zhang, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Catching both gray and black swans: open-set supervised anomaly detection
\(\cdot\) C. Ding, G. Pan, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
RigidFlow: self-supervised scene flow learning on point clouds by local rigidity prior
\(\cdot\) R. Li, C. Zhang, G. Lin, Z. Wang, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
Retrieval augmented classification for long-tail visual recognition
\(\cdot\) A. Long, W. Yin, T. Ajanthan, V. Nguyen, P. Purkait, R. Garg, A. Blair, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar
FreeSOLO: learning to segment objects without annotations
\(\cdot\) X. Wang, Z. Yu, S. De Mello, J. Kautz, A. Anandkumar, C. Shen, J. Alvarez.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
TopFormer: token pyramid transformer for mobile semantic segmentation
\(\cdot\) W. Zhang, Z. Huang, G. Yu, T. Chen, G. Luo, X. Wang, W. Liu, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
AQD: towards accurate quantized object detection
\(\cdot\) P. Chen, J. Liu, B. Zhuang, M. Tan, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
1. Oral presentation.
Learning affinity-aware upsampling for deep image matting
\(\cdot\) Y. Dai, H. Lu, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Graph attention tracking
\(\cdot\) D. Guo, Y. Shao, Y. Cui, Z. Wang, L. Zhang, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
DyCo3D: robust instance segmentation of 3d point clouds through dynamic convolution
\(\cdot\) T. He, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
HCRF-Flow: scene flow from point clouds with continuous high-order CRFs and position-aware flow embedding
\(\cdot\) R. Li, G. Lin, T. He, F. Liu, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) bibtex google scholar semantic scholar
Generic perceptual loss for modelling structured output dependencies
\(\cdot\) Y. Liu, W. Yin, Y. Chen, H. Chen, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) bibtex google scholar semantic scholar
FCPose: fully convolutional multi-person pose estimation with dynamic instance-aware convolutions
\(\cdot\) W. Mao, Z. Tian, X. Wang, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) bibtex google scholar semantic scholar project webpage
Feature decomposition and reconstruction learning for effective facial expression recognition
\(\cdot\) D. Ruan, Y. Yan, S. Lai, Z. Chai, C. Shen, H. Wang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) bibtex google scholar semantic scholar
Learning spatial-semantic relationship for facial attribute recognition with limited labeled data
\(\cdot\) Y. Shu, Y. Yan, S. Chen, J. Xue, C. Shen, H. Wang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) bibtex google scholar semantic scholar
BoxInst: high-performance instance segmentation with box annotations
\(\cdot\) Z. Tian, C. Shen, X. Wang, H. Chen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Dense contrastive learning for self-supervised visual pre-training
\(\cdot\) X. Wang, R. Zhang, C. Shen, T. Kong, L. Li.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
1. Oral presentation.
End-to-end video instance segmentation with Transformers
\(\cdot\) Y. Wang, Z. Xu, X. Wang, C. Shen, B. Cheng, H. Shen, H. Xia.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
1. Oral presentation.
Learning to recover 3D scene shape from a single image
\(\cdot\) W. Yin, J. Zhang, O. Wang, S. Niklaus, L. Mai, S. Chen, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
1. Listed as one of the Best Paper Candidates, 32 out of about 6000 submissions.
DoDNet: learning to segment multi-organ and tumors from multiple partially labeled datasets
\(\cdot\) J. Zhang, Y. Xie, Y. Xia, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
BlendMask: top-down meets bottom-up for instance segmentation
\(\cdot\) H. Chen, K. Sun, Z. Tian, C. Shen, Y. Huang, Y. Yan.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
1. Oral presentation.
ABCNet: arbitrarily-shaped scene text spotting with adaptive Bezier-curve network in real time
\(\cdot\) Y. Liu, H. Chen, C. Shen, T. He, L. Jin, L. Wang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
1. Oral presentation.
Self-trained deep ordinal regression for end-to-end video anomaly detection
\(\cdot\) G. Pang, C. Yan, C. Shen, A. van den Hengel, X. Bai.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar
REVERIE: remote embodied visual referring expression in real indoor environments
\(\cdot\) Y. Qi, Q. Wu, P. Anderson, X. Wang, W. Wang, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar
1. Oral presentation.
NAS-FCOS: fast neural architecture search for object detection
\(\cdot\) N. Wang, Y. Gao, H. Chen, P. Wang, Z. Tian, C. Shen, Y. Zhang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
On the general value of evidence, and bilingual scene-text visual question answering
\(\cdot\) X. Wang, Y. Liu, C. Shen, C. Ng, C. Luo, L. Jin, C. Chan, A. van den Hengel, L. Wang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar
PolarMask: single shot instance segmentation with polar representation
\(\cdot\) E. Xie, P. Sun, X. Song, W. Wang, X. Liu, D. Liang, C. Shen, P. Luo.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
1. Oral presentation.
Context prior for scene segmentation
\(\cdot\) C. Yu, J. Wang, C. Gao, G. Yu, C. Shen, N. Sang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar
DeepEMD: few-shot image classification with differentiable earth mover's distance and structured classifiers
\(\cdot\) C. Zhang, Y. Cai, G. Lin, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
1. Oral presentation.
Memory-efficient hierarchical neural architecture search for image denoising
\(\cdot\) H. Zhang, Y. Li, H. Chen, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Mask encoding for single shot instance segmentation
\(\cdot\) R. Zhang, Z. Tian, C. Shen, M. You, Y. Yan.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Training quantized neural networks with a full-precision auxiliary module
\(\cdot\) B. Zhuang, L. Liu, M. Tan, C. Shen, I. Reid.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar
1. Oral presentation.
Knowledge adaptation for efficient semantic segmentation
\(\cdot\) T. He, C. Shen, Z. Tian, D. Gong, C. Sun, Y. Yan.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Visual question answering as reading comprehension
\(\cdot\) H. Li, P. Wang, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Fast neural architecture search of compact semantic segmentation models via auxiliary cells
\(\cdot\) V. Nekrasov, H. Chen, C. Shen, I. Reid.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Decoders matter for semantic segmentation: data-dependent decoding enables flexible feature aggregation
\(\cdot\) Z. Tian, T. He, C. Shen, Y. Yan.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Neighbourhood watch: referring expression comprehension via language-guided graph attention networks
\(\cdot\) P. Wang, Q. Wu, J. Cao, C. Shen, L. Gao, A. vanden Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Associatively segmenting instances and semantics in point clouds
\(\cdot\) X. Wang, S. Liu, X. Shen, C. Shen, J. Jia.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Attention-guided network for ghost-free high dynamic range imaging
\(\cdot\) Q. Yan, D. Gong, Q. Shi, A. van den Hengel, C. Shen, I. Reid, Y. Zhang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
CANet: class-agnostic segmentation networks with iterative refinement and attentive few-shot learning
\(\cdot\) C. Zhang, G. Lin, F. Liu, R. Yao, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Mind your neighbours: image annotation with metadata neighbourhood graph co-attention networks
\(\cdot\) J. Zhang, Q. Wu, J. Zhang, C. Shen, J. Lu.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
\(\cdot\) link bibtex google scholar semantic scholar
Structured binary neural networks for accurate image classification and semantic segmentation
\(\cdot\) B. Zhuang, C. Shen, M. Tan, L. Liu, I. Reid.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
FSRNet: end-to-end learning face super-resolution with facial priors
\(\cdot\) Y. Chen, Y. Tai, X. Liu, C. Shen, J. Yang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
An end-to-end textspotter with explicit alignment and attention
\(\cdot\) T. He, Z. Tian, W. Huang, C. Shen, Y. Qiao, C. Sun.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Visual question answering with memory-augmented networks
\(\cdot\) C. Ma, C. Shen, A. Dick, Q. Wu, P. Wang, A. van den Hengel, I. Reid.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Bootstrapping the performance of webly supervised semantic segmentation
\(\cdot\) T. Shen, G. Lin, C. Shen, I. Reid.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
\(\cdot\) bibtex google scholar semantic scholar project webpage
VITAL: visual tracking via adversarial learning
\(\cdot\) Y. Song, C. Ma, X. Wu, L. Gong, L. Bao, W. Zuo, C. Shen, R. Lau, M. Yang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Repulsion loss: detecting pedestrians in a crowd
\(\cdot\) X. Wang, T. Xiao, Y. Jiang, S. Shao, J. Sun, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar
1. Others have implemented our paper: Repulsion loss in SSD and Repulsion loss in RetinaNet.
Are you talking to me? reasoned visual dialog generation through adversarial learning
\(\cdot\) Q. Wu, P. Wang, C. Shen, I. Reid, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Monocular relative depth perception with web stereo data supervision
\(\cdot\) K. Xian, C. Shen, Z. Cao, H. Lu, Y. Xiao, R. Li, Z. Luo.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
\(\cdot\) bibtex google scholar semantic scholar
Towards effective low-bitwidth convolutional neural networks
\(\cdot\) B. Zhuang, C. Shen, M. Tan, L. Liu, I. Reid.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Parallel attention: a unified framework for visual object discovery through dialogs and queries
\(\cdot\) B. Zhuang, Q. Wu, C. Shen, I. Reid, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar
From motion blur to motion flow: a deep learning solution for removing heterogeneous motion blur
\(\cdot\) D. Gong, J. Yang, L. Liu, Y. Zhang, I. Reid, C. Shen, A. van den Hengel, Q. Shi.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Sequential person recognition in photo albums with a recurrent network
\(\cdot\) Y. Li, G. Lin, B. Zhuang, L. Liu, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
RefineNet: multi-path refinement networks for high-resolution semantic segmentation
\(\cdot\) G. Lin, A. Milan, C. Shen, I. Reid.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
1. Light-weight RefineNet with Pytorch code.
Multi-attention network for one shot learning
\(\cdot\) P. Wang, L. Liu, C. Shen, Z. Huang, A. van den Hengel, H. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
\(\cdot\) pdf bibtex google scholar semantic scholar
The VQA-machine: learning how to use existing vision algorithms to answer new questions
\(\cdot\) P. Wang, Q. Wu, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Attend in groups: a weakly-supervised deep learning framework for learning from web data
\(\cdot\) B. Zhuang, L. Liu, Y. Li, C. Shen, I. Reid.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Efficient piecewise training of deep structured models for semantic segmentation
\(\cdot\) G. Lin, C. Shen, A. van dan Hengel, I. Reid.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Less is more: zero-shot learning from online textual documents with noise suppression
\(\cdot\) R. Qiao, L. Liu, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
\(\cdot\) arXiv bibtex google scholar semantic scholar
What's wrong with that object? identifying irregular object from images by modelling the detection score distribution
\(\cdot\) P. Wang, L. Liu, C. Shen, Z. Huang, A. van den Hengel, H. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
\(\cdot\) arXiv bibtex google scholar semantic scholar
What value do explicit high level concepts have in vision to language problems
\(\cdot\) Q. Wu, C. Shen, L. Liu, A. Dick, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Ask me anything: free-form visual question answering based on knowledge from external sources
\(\cdot\) Q. Wu, P. Wang, C. Shen, A. Dick, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Fast training of triplet-based deep binary embedding networks
\(\cdot\) B. Zhuang, G. Lin, C. Shen, I. Reid.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs
\(\cdot\) B. Li, C. Shen, Y. Dai, A. van den Hengel, M. He.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
\(\cdot\) pdf bibtex google scholar semantic scholar
Mid-level deep pattern mining
\(\cdot\) Y. Li, L. Liu, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Deep convolutional neural fields for depth estimation from a single image
\(\cdot\) F. Liu, C. Shen, G. Lin.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
The treasure beneath convolutional layers: cross convolutional layer pooling for image classification
\(\cdot\) L. Liu, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Learning to rank in person re-identification with metric ensembles
\(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Supervised discrete hashing
\(\cdot\) F. Shen, C. Shen, W. Liu, H. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
\(\cdot\) pdf bibtex google scholar semantic scholar project webpage
Learning graph structure for multi-label image classification via clique generation
\(\cdot\) M. Tan, Q. Shi, A. van den Hengel, C. Shen, J. Gao, F. Hu, Z. Zhang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
\(\cdot\) pdf bibtex google scholar semantic scholar
Efficient SDP inference for fully-connected CRFs based on low-rank decomposition
\(\cdot\) P. Wang, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Fast supervised hashing with decision trees for high-dimensional data
\(\cdot\) G. Lin, C. Shen, Q. Shi, A. van den Hengel, D. Suter.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’14), 2014.
\(\cdot\) arXiv link bibtex google scholar semantic scholar project webpage
Learning compact binary codes for visual tracking
\(\cdot\) X. Li, C. Shen, A. Dick, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), 2013.
\(\cdot\) link pdf bibtex google scholar semantic scholar
Inductive hashing on manifolds
\(\cdot\) F. Shen, C. Shen, Q. Shi, A. van den Hengel, Z. Tang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), 2013.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
A fast semidefinite approach to solving binary quadratic problems
\(\cdot\) P. Wang, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), 2013.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
1. Oral presentation, 60 out of 1870 submissions.
Bilinear programming for human activity recognition with unknown MRF graphs
\(\cdot\) Z. Wang, Q. Shi, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), 2013.
\(\cdot\) link pdf bibtex google scholar semantic scholar
Part-based visual tracking with online latent structural learning
\(\cdot\) R. Yao, Q. Shi, C. Shen, Y. Zhang, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), 2013.
\(\cdot\) link pdf bibtex google scholar semantic scholar project webpage
Non-sparse linear representations for visual tracking with online reservoir metric learning
\(\cdot\) X. Li, C. Shen, Q. Shi, A. Dick, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’12), 2012.
\(\cdot\) arXiv pdf bibtex google scholar semantic scholar
Sharing features in multi-class boosting via group sparsity
\(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’12), 2012.
\(\cdot\) pdf bibtex google scholar semantic scholar
Real-time visual tracking using compressive sensing
\(\cdot\) H. Li, C. Shen, Q. Shi.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’11), 2011.
\(\cdot\) pdf bibtex google scholar semantic scholar
A generalized probabilistic framework for compact codebook creation
\(\cdot\) L. Liu, L. Wang, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’11), 2011.
\(\cdot\) pdf bibtex google scholar semantic scholar
A direct formulation for totally-corrective multi-class boosting
\(\cdot\) C. Shen, Z. Hao.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’11), 2011.
\(\cdot\) pdf bibtex google scholar semantic scholar
A scalable dual approach to semidefinite metric learning
\(\cdot\) C. Shen, J. Kim, L. Wang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’11), 2011.
\(\cdot\) pdf bibtex google scholar semantic scholar
Is face recognition really a compressive sensing problem?
\(\cdot\) Q. Shi, A. Eriksson, A. van den Hengel, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’11), 2011.
\(\cdot\) pdf bibtex google scholar semantic scholar
Rapid face recognition using hashing
\(\cdot\) Q. Shi, H. Li, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’10), 2010.
\(\cdot\) pdf bibtex google scholar semantic scholar
Efficiently training a better visual detector with sparse eigenvectors
\(\cdot\) S. Paisitkriangkrai, C. Shen, J. Zhang.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’09), 2009.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
Kernel-based tracking from a probabilistic viewpoint
\(\cdot\) Q. Nguyen, A. Robles-Kelly, C. Shen.
\(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’07), 2007.
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Efficient decoder-free object detection with transformers
\(\cdot\) P. Chen, M. Zhang, Y. Shen, K. Sheng, Y. Gao, X. Sun, K. Li, C. Shen.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’22), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar
DisCo: remedying self-supervised learning on lightweight models with distilled contrastive learning
\(\cdot\) Y. Gao, J. Zhuang, S. Lin, H. Cheng, X. Sun, K. Li, C. Shen.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar project webpage
1. Oral presentation.
PointInst3D: segmenting 3D instances by points
\(\cdot\) T. He, W. Yin, C. Shen, A. van den Hengel.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’22), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Poseur: direct human pose regression with transformers
\(\cdot\) W. Mao, Y. Ge, C. Shen, Z. Tian, X. Wang, Z. Wang, A. van den Hengel.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’22), 2022.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Learning and memorizing representative prototypes for 3D point cloud semantic and instance segmentation
\(\cdot\) T. He, D. Gong, Z. Tian, C. Shen.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) bibtex google scholar semantic scholar
Instance-aware embedding for point cloud instance segmentation
\(\cdot\) T. He, Y. Liu, C. Shen, X. Wang, C. Sun.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) bibtex google scholar semantic scholar
Weighing counts: sequential crowd counting by reinforcement learning
\(\cdot\) L. Liu, H. Lu, H. Zou, H. Xiong, Z. Cao, C. Shen.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Efficient semantic video segmentation with per-frame inference
\(\cdot\) Y. Liu, C. Shen, C. Yu, J. Wang.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Conditional convolutions for instance segmentation
\(\cdot\) Z. Tian, C. Shen, H. Chen.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
1. Oral presentation.
Soft expert reward learning for vision-and-language navigation
\(\cdot\) H. Wang, Q. Wu, C. Shen.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) bibtex google scholar semantic scholar
AE TextSpotter: learning visual and linguistic representation for ambiguous text spotting
\(\cdot\) W. Wang, X. Liu, X. Ji, E. Xie, D. Liang, Z. Yang, T. Lu, C. Shen, P. Luo.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) bibtex google scholar semantic scholar
Scene text image super-resolution in the wild
\(\cdot\) W. Wang, E. Xie, X. Liu, W. Wang, D. Liang, C. Shen, X. Bai.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar
SOLO: segmenting objects by locations
\(\cdot\) X. Wang, T. Kong, C. Shen, Y. Jiang, L. Li.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Segmenting transparent objects in the wild
\(\cdot\) E. Xie, W. Wang, W. Wang, M. Ding, C. Shen, P. Luo.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Representative graph neural network
\(\cdot\) C. Yu, Y. Liu, C. Gao, C. Shen, N. Sang.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Learning to predict crisp boundaries
\(\cdot\) R. Deng, C. Shen, S. Liu, H. Wang, X. Liu.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Goal-oriented visual question generation via intermediate rewards
\(\cdot\) J. Zhang, Q. Wu, C. Shen, J. Zhang, J. Lu, A. van den Hengel.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Image co-localization by mimicking a good detector's confidence score distribution
\(\cdot\) Y. Li, L. Liu, C. Shen, A. van den Hengel.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’16), 2016.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Cluster sparsity field for hyperspectral imagery denoising
\(\cdot\) L. Zhang, W. Wei, Y. Zhang, C. Shen, A. van den Hengel, Q. Shi.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’16), 2016.
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Optimizing ranking measures for compact binary code learning
\(\cdot\) G. Lin, C. Shen, J. Wu.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’14), 2014.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Strengthening the effectiveness of pedestrian detection with spatially pooled features
\(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’14), 2014.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Robust tracking with weighted online structured learning
\(\cdot\) R. Yao, Q. Shi, C. Shen, Y. Zhang, A. van den Hengel.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’12), 2012.
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LACBoost and FisherBoost: optimally building cascade classifiers
\(\cdot\) C. Shen, P. Wang, H. Li.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’10), 2010.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
A fast algorithm for creating a compact and discriminative visual codebook
\(\cdot\) L. Wang, L. Zhou, C. Shen.
\(\cdot\) Proc. European Conference on Computer Vision (ECCV’08), 2008.
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Zolly: zoom focal length correctly for perspective-distorted human mesh reconstruction
\(\cdot\) W. Wang, Y. Ge, H. Mei, Z. Cai, Q. Sun, C. Shen, Y. Wang, L. Yang, T. Komura.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
\(\cdot\) bibtex google scholar semantic scholar
1. Oral presentation.
SegGPT: towards segmenting everything in context
\(\cdot\) X. Wang, X. Zhang, Y. Cao, W. Wang, C. Shen, T. Huang.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Diffumask: synthesizing images with pixel-level annotations for semantic segmentation using diffusion models
\(\cdot\) W. Wu, Y. Zhao, M. Shou, H. Zhou, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Pose-free 3d scene reconstruction with frozen depth models
\(\cdot\) G. Xu, W. Yin, H. Chen, C. Shen, K. Cheng, F. Zhao.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
\(\cdot\) bibtex google scholar semantic scholar
Metric3D: towards zero-shot metric 3d prediction from a single image
\(\cdot\) W. Yin, C. Zhang, H. Chen, Z. Cai, G. Yu, K. Wang, X. Chen, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar
CTVIS: consistent training for online video instance segmentation
\(\cdot\) K. Ying, Q. Zhong, W. Mao, Z. Wang, H. Chen, L. Wu, Y. Liu, C. Fan, Y. Zhuge, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Robust geometry-preserving depth estimation using differentiable rendering
\(\cdot\) C. Zhang, W. Yin, G. Yu, Z. Wang, T. Chen, B. Fu, J. Zhou, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
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Generative prompt model for weakly supervised object localization
\(\cdot\) Y. Zhao, Q. Ye, W. Wu, C. Shen, F. Wan.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Segprompt: boosting open-world segmentation via category-level prompt learning
\(\cdot\) M. Zhu, H. Li, H. Chen, C. Fan, W. Mao, C. Jing, Y. Liu, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
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FATNN: fast and accurate ternary neural networks
\(\cdot\) P. Chen, B. Zhuang, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Channel-wise knowledge distillation for dense prediction
\(\cdot\) C. Shu, Y. Liu, J. Gao, L. Xu, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Occluded person re-identification with single-scale global representations
\(\cdot\) C. Yan, G. Pang, J. Jiao, X. Bai, X. Feng, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
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1. Oral presentation.
BV-Person: a large-scale dataset for bird-view person re-identification
\(\cdot\) C. Yan, G. Pang, L. Wang, J. Jiao, X. Feng, C. Shen, J. Li.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
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A simple baseline for semi-supervised semantic segmentation with strong data augmentation
\(\cdot\) J. Yuan, Y. Liu, C. Shen, Z. Wang, H. Li.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Meta navigator: search for a good adaptation policy for few-shot learning
\(\cdot\) C. Zhang, H. Ding, G. Lin, R. Li, C. Wang, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Indices matter: learning to index for deep image matting
\(\cdot\) H. Lu, Y. Dai, C. Shen, S. Xu.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
FCOS: fully convolutional one-stage object detection
\(\cdot\) Z. Tian, C. Shen, H. Chen, T. He.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Efficient and accurate arbitrary-shaped text detection with pixel aggregation network
\(\cdot\) W. Wang, E. Xie, X. Song, Y. Zang, W. Wang, T. Lu, G. Yu, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
\(\cdot\) bibtex google scholar semantic scholar
From open set to closed set: counting objects by spatial divide-and-conquer
\(\cdot\) H. Xiong, H. Lu, C. Liu, L. Liu, Z. Cao, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Enforcing geometric constraints of virtual normal for depth prediction
\(\cdot\) W. Yin, Y. Liu, C. Shen, Y. Yan.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Exploiting temporal consistency for real-time video depth estimation
\(\cdot\) H. Zhang, C. Shen, Y. Li, Y. Cao, Y. Liu, Y. Yan.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Self-training with progressive augmentation for unsupervised cross-domain person re-identification
\(\cdot\) X. Zhang, J. Cao, C. Shen, M. You.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Adversarial PoseNet: a structure-aware convolutional network for human pose estimation
\(\cdot\) Y. Chen, C. Shen, X. Wei, L. Liu, J. Yang.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Towards end-to-end text spotting with convolutional recurrent neural networks
\(\cdot\) H. Li, P. Wang, C. Shen.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Semi-global weighted least squares in image filtering
\(\cdot\) W. Liu, X. Chen, C. Shen, Z. Liu, J. Yang.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
When unsupervised domain adaptation meets tensor representations
\(\cdot\) H. Lu, L. Zhang, Z. Cao, W. Wei, K. Xian, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
\(\cdot\) bibtex google scholar semantic scholar
Towards context-aware interaction recognition
\(\cdot\) B. Zhuang, L. Liu, C. Shen, I. Reid.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Hyperspectral compressive sensing using manifold-structured sparsity prior
\(\cdot\) L. Zhang, W. Wei, Y. Zhang, F. Li, C. Shen, Q. Shi.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’15), 2015.
\(\cdot\) pdf bibtex google scholar semantic scholar
Contextual hypergraph modeling for salient object detection
\(\cdot\) X. Li, Y. Li, C. Shen, A. Dick, A. van den Hengel.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’13), 2013.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
A general two-step approach to learning-based hashing
\(\cdot\) G. Lin, C. Shen, D. Suter, A. van den Hengel.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’13), 2013.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Efficient pedestrian detection by directly optimizing the partial area under the ROC curve
\(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’13), 2013.
\(\cdot\) arXiv pdf bibtex google scholar semantic scholar
Dictionary learning and sparse coding on Grassmann manifolds: an extrinsic solution
\(\cdot\) M. Harandi, C. Sanderson, C. Shen, B. Lovell.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’13), 2013.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Graph mode-based contextual kernels for robust SVM tracking
\(\cdot\) X. Li, A. Dick, H. Wang, C. Shen, A. van den Hengel.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’11), 2011.
\(\cdot\) pdf bibtex google scholar semantic scholar
Fast global kernel density mode seeking with application to localisation and tracking
\(\cdot\) C. Shen, M. Brooks, A. van den Hengel.
\(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’05), 2005.
\(\cdot\) link pdf bibtex google scholar semantic scholar
1. Oral presentation, 45 out of 1200 submissions.
Matcher: segment anything with one shot using all-purpose feature matching
\(\cdot\) Y. Liu, M. Zhu, H. Li, H. Chen, X. Wang, C. Shen.
\(\cdot\) Proc. International Conference on Learning Representations (ICLR’24), 2024.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
De novo protein design using geometric vector field networks
\(\cdot\) W. Mao, M. Zhu, Z. Sun, S. Shen, L. Wu, H. Chen, C. Shen.
\(\cdot\) Proc. International Conference on Learning Representations (ICLR’24), 2024.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
1. Spotlight presentation.
Object-aware inversion and reassembly for image editing
\(\cdot\) Z. Yang, D. Gui, W. Wang, H. Chen, B. Zhuang, C. Shen.
\(\cdot\) Proc. International Conference on Learning Representations (ICLR’24), 2024.
\(\cdot\) arXiv link bibtex google scholar semantic scholar project webpage
Conditional positional encodings for vision transformers
\(\cdot\) X. Chu, Z. Tian, B. Zhang, X. Wang, X. Wei, H. Xia, C. Shen.
\(\cdot\) Proc. International Conference on Learning Representations (ICLR’23), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar
On the trajectory regularity of ODE-based diffusion sampling
\(\cdot\) D. Chen, Z. Zhou, C. Wang, C. Shen, S. Lyu.
\(\cdot\) Proc. International Conference on Machine Learning (ICML’24), 2024.
\(\cdot\) bibtex google scholar semantic scholar
Floating anchor diffusion model for multi-motif scaffolding
\(\cdot\) K. Liu, S. Shen, W. Mao, X. Jiao, Z. Sun, H. Chen, C. Shen.
\(\cdot\) Proc. International Conference on Machine Learning (ICML’24), 2024.
\(\cdot\) bibtex google scholar semantic scholar
Generative active learning for long-tailed instance segmentation
\(\cdot\) M. Zhu, C. Fan, H. Chen, Y. Liu, W. Mao, X. Xu, C. Shen.
\(\cdot\) Proc. International Conference on Machine Learning (ICML’24), 2024.
\(\cdot\) bibtex google scholar semantic scholar
Adversarial learning with local coordinate coding
\(\cdot\) J. Cao, Y. Guo, Q. Wu, C. Shen, J. Huang, M. Tan.
\(\cdot\) Proc. International Conference on Machine Learning (ICML’18), 2018.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Learning hash functions using column generation
\(\cdot\) X. Li, G. Lin, C. Shen, A. van den Hengel, A. Dick.
\(\cdot\) Proc. International Conference on Machine Learning (ICML’13), 2013.
\(\cdot\) arXiv pdf bibtex google scholar semantic scholar project webpage
1. Oral presentation.
Is margin preserved after random projection?
\(\cdot\) Q. Shi, C. Shen, R. Hill, A. van den Hengel.
\(\cdot\) Proc. International Conference on Machine Learning (ICML’12), 2012.
\(\cdot\) arXiv link bibtex google scholar semantic scholar
1. This work provides an analysis of margin distortion under random projections, the conditions under which margins are preserved, and presents bounds on the margin distortion.
DatasetDM: synthesizing data with perception annotations using diffusion models
\(\cdot\) W. Wu, Y. Zhao, H. Chen, Y. Gu, R. Zhao, Y. He, H. Zhou, M. Shou, C. Shen.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’23), 2023.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
PyramidCLIP: hierarchical feature alignment for vision-language model pretraining
\(\cdot\) Y. Gao, J. Liu, Z. Xu, J. Zhang, K. Li, R. Ji, C. Shen.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
Adv-attribute: inconspicuous and transferable adversarial attack on face recognition
\(\cdot\) S. Jia, B. Yin, T. Yao, S. Ding, C. Shen, X. Yang, C. Ma.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
Multi-dataset training of transformers for robust action recognition
\(\cdot\) J. Liang, E. Zhang, J. Zhang, C. Shen.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
Text-adaptive multiple visual prototype matching for video-text retrieval
\(\cdot\) C. Lin, A. Wu, J. Liang, J. Zhang, W. Ge, W. Zheng, C. Shen.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
Fully convolutional one-stage 3D object detection on LiDAR range images
\(\cdot\) Z. Tian, X. Chu, X. Wang, X. Wei, C. Shen.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
SegViT: semantic segmentation with plain vision transformers
\(\cdot\) B. Zhang, Z. Tian, Q. Tang, X. Chu, X. Wei, C. Shen, Y. Liu.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
Hierarchical normalization for robust monocular depth estimation
\(\cdot\) C. Zhang, W. Yin, Z. Wang, G. Yu, B. Fu, C. Shen.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
DENSE: data-free one-shot federated learning
\(\cdot\) J. Zhang, C. Chen, B. Li, L. Lyu, S. Wu, S. Ding, C. Shen, C. Wu.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
\(\cdot\) bibtex google scholar semantic scholar
Twins: revisiting the design of spatial attention in vision transformers
\(\cdot\) X. Chu, Z. Tian, Y. Wang, B. Zhang, H. Ren, X. Wei, H. Xia, C. Shen.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Dynamic neural representational decoders for high-resolution semantic segmentation
\(\cdot\) B. Zhang, Y. Liu, Z. Tian, C. Shen.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’21), 2021.
\(\cdot\) arXiv bibtex google scholar semantic scholar
SOLOv2: dynamic and fast instance segmentation
\(\cdot\) X. Wang, R. Zhang, T. Kong, L. Li, C. Shen.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’20), 2020.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Unsupervised scale-consistent depth and ego-motion learning from monocular video
\(\cdot\) J. Bian, Z. Li, N. Wang, H. Zhan, C. Shen, M. Cheng, I. Reid.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar project webpage
Multi-marginal wasserstein GAN
\(\cdot\) J. Cao, L. Mo, Y. Zhang, K. Jia, C. Shen, M. Tan.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’19), 2019.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Image restoration using very deep fully convolutional encoder-decoder networks with symmetric skip connections
\(\cdot\) X. Mao, C. Shen, Y. Yang.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’16), 2016.
\(\cdot\) arXiv link bibtex google scholar semantic scholar project webpage
1. Others have implemented our paper.
Deeply learning the messages in message passing inference
\(\cdot\) G. Lin, C. Shen, I. Reid, A. van den Hengel.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’15), 2015.
\(\cdot\) arXiv pdf bibtex google scholar semantic scholar
Encoding high dimensional local features by sparse coding based Fisher vectors
\(\cdot\) L. Liu, C. Shen, L. Wang, A. van den Hengel, C. Wang.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’14), 2014.
\(\cdot\) arXiv bibtex google scholar semantic scholar
Positive semidefinite metric learning with boosting
\(\cdot\) C. Shen, J. Kim, L. Wang, A. van den Hengel.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’09), 2009.
\(\cdot\) arXiv pdf bibtex google scholar semantic scholar project webpage
PSDBoost: matrix-generation linear programming for positive semidefinite matrices learning
\(\cdot\) C. Shen, A. Welsh, L. Wang.
\(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’08), 2008.
\(\cdot\) pdf bibtex google scholar semantic scholar