HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2017-October, Issue , 2017, Pages 350-359

  Liu, Xihui ^a,b   Zhao, Haiyu ^b   Tian, Maoqing ^b   Sheng, Lu ^a   Shao, Jing ^b   Yi, Shuai ^b   Yan, Junjie ^b   Wang, Xiaogang ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^b SENSETIME RESEARCH   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DEEP LEARNING; DEEP NEURAL NETWORKS; FOOTBRIDGES; NEURAL NETWORKS; SECURITY SYSTEMS; SEMANTICS;

ATTRIBUTE RECOGNITION; COMPUTER VISION SYSTEM; CONVOLUTIONAL NEURAL NETWORK; DISCRIMINATIVE FEATURES; FEATURE REPRESENTATION; INTELLIGENT VIDEO SURVEILLANCE; PERSON RE IDENTIFICATIONS; SEMANTIC LEVELS;

COMPUTER VISION;

EID: 85041891926     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2017.46     Document Type: Conference Paper

References (38)

1. E. Ahmed, M. Jones, and T. K. Marks. An improved deep learning architecture for person re-identification. In CVPR, 2015
2. J. Ba, V. Mnih, and K. Kavukcuoglu. Multiple object recognition with visual attention. ArXiv preprint arXiv:1412.7755, 2014
3. D. Chen, Z. Yuan, B. Chen, and N. Zheng. Similarity learning with spatial constraints for person re-identification. In CVPR, 2016
4. L.-C. Chen, Y. Yang, J. Wang, W. Xu, and A. L. Yuille. Attention to scale: Scale-aware semantic image segmentation. In CVPR, 2016
5. D. Cheng, Y. Gong, S. Zhou, J. Wang, and N. Zheng. Person re-identification by multi-channel parts-based cnn with improved triplet loss function. In CVPR, 2016
6. M. Cornia, L. Baraldi, G. Serra, and R. Cucchiara. A deep multi-level network for saliency prediction. ArXiv preprint arXiv:1609.01064, 2016
7. Y. Deng, P. Luo, C. C. Loy, and X. Tang. Pedestrian attribute recognition at far distance. In Proceedings of the 22nd ACM international conference on Multimedia, 2014
8. D. Gray, S. Brennan, and H. Tao. Evaluating appearance models for recognition, reacquisition, and tracking. In Proc. IEEE International Workshop on Performance Evaluation for Tracking and Surveillance (PETS), 2007
9. D. Gray and H. Tao. Viewpoint invariant pedestrian recognition with an ensemble of localized features. In ECCV, 2008
10. S. Ioffe and C. Szegedy. Batch normalization: Accelerating deep network training by reducing internal covariate shift. ArXiv preprint arXiv:1502.03167, 2015
11. C. Jose and F. Fleuret. Scalable metric learning via weighted approximate rank component analysis. ArXiv preprint arXiv:1603.00370, 2016
12. M. Koestinger, M. Hirzer, P. Wohlhart, P. M. Roth, and H. Bischof. Large scale metric learning from equivalence constraints. In CVPR, 2012
13. D. Li, X. Chen, and K. Huang. Multi-attribute learning for pedestrian attribute recognition in surveillance scenarios. In Pattern Recognition (ACPR), 2015 3rd IAPR Asian Conference on, 2015
14. D. Li, Z. Zhang, X. Chen, H. Ling, and K. Huang. A richly annotated dataset for pedestrian attribute recognition. ArXiv preprint arXiv:1603.07054, 2016
15. S. Li, T. Xiao, H. Li, B. Zhou, D. Yue, and X. Wang. Person search with natural language description. In CVPR, 2017
16. W. Li, R. Zhao, T. Xiao, and X.Wang. Deepreid: Deep filter pairing neural network for person re-identification. In CVPR, 2014
17. S. Liao, Y. Hu, X. Zhu, and S. Z. Li. Person re-identification by local maximal occurrence representation and metric learning. In CVPR, 2015
18. J. Lu, J. Yang, D. Batra, and D. Parikh. Hierarchical question-image co-attention for visual question answering. In NIPS, 2016
19. T. Matsukawa, T. Okabe, E. Suzuki, and Y. Sato. Hierarchical Gaussian descriptor for person re-identification. In CVPR, 2016
20. V. Mnih, N. Heess, A. Graves, et al. Recurrent models of visual attention. In NIPS, 2014
21. A. Newell, K. Yang, and J. Deng. Stacked hourglass networks for human pose estimation. In ECCV, 2016
22. B. Prosser, W.-S. Zheng, S. Gong, T. Xiang, and Q. Mary. Person re-identification by support vector ranking. In BMVC, 2010
23. C. Su, S. Zhang, J. Xing, W. Gao, and Q. Tian. Deep attributes driven multi-camera person re-identification. In ECCV, 2016
24. P. Sudowe, H. Spitzer, and B. Leibe. Person attribute recognition with a jointly-trained holistic cnn model. In CVPR, 2015
25. E. Ustinova, Y. Ganin, and V. Lempitsky. Multiregion bilinear convolutional neural networks for person reidentification. ArXiv preprint arXiv:1512.05300, 2015
26. R. R. Varior, M. Haloi, and G. Wang. Gated siamese convolutional neural network architecture for human reidentification. In ECCV, 2016
27. R. R. Varior, B. Shuai, J. Lu, D. Xu, and G. Wang. A siamese long short-term memory architecture for human reidentification. In ECCV, 2016
28. R. J. Williams. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Machine learning, 8(3-4):229-256, 1992
29. L. Wu, C. Shen, and A. v. d. Hengel. Personnet: person re-identification with deep convolutional neural networks. ArXiv preprint arXiv:1601.07255, 2016
30. T. Xiao, H. Li,W. Ouyang, and X.Wang. Learning deep feature representations with domain guided dropout for person re-identification. In CVPR, 2016
31. T. Xiao, S. Li, B. Wang, L. Lin, and X. Wang. Joint detection and identification feature learning for person search. In CVPR, 2017
32. T. Xiao, Y. Xu, K. Yang, J. Zhang, Y. Peng, and Z. Zhang. The application of two-level attention models in deep convolutional neural network for fine-grained image classification. In CVPR, 2015
33. H. Xu and K. Saenko. Ask, attend and answer: Exploring question-guided spatial attention for visual question answering. In ECCV, 2016
34. K. Xu, J. Ba, R. Kiros, K. Cho, A. C. Courville, R. Salakhutdinov, R. S. Zemel, and Y. Bengio. Show, attend and tell: Neural image caption generation with visual attention. In ICML, 2015
35. S. Zagoruyko and N. Komodakis. Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer. ArXiv preprint arXiv:1612.03928, 2016
36. L. Zhang, T. Xiang, and S. Gong. Learning a discriminative null space for person re-identification. ArXiv preprint arXiv:1603.02139, 2016
37. N. Zhang, M. Paluri, M. Ranzato, T. Darrell, and L. Bourdev. Panda: Pose aligned networks for deep attribute modeling. In CVPR, 2014
38. L. Zheng, L. Shen, L. Tian, S. Wang, J. Wang, and Q. Tian. Scalable person re-identification: A benchmark. In ICCV, 2015.