Multiple instance detection network with online instance classifier refinement P Tang, X Wang, X Bai, W Liu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 518 | 2017 |
Revisiting multiple instance neural networks X Wang, Y Yan, P Tang, X Bai, W Liu Pattern recognition 74, 15-24, 2018 | 477 | 2018 |
Pcl: Proposal cluster learning for weakly supervised object detection P Tang, X Wang, S Bai, W Shen, X Bai, W Liu, A Yuille IEEE transactions on pattern analysis and machine intelligence 42 (1), 176-191, 2018 | 404 | 2018 |
Weakly supervised region proposal network and object detection P Tang, X Wang, A Wang, Y Yan, W Liu, J Huang, A Yuille Proceedings of the European conference on computer vision (ECCV), 352-368, 2018 | 236 | 2018 |
Semi-supervised 3D abdominal multi-organ segmentation via deep multi-planar co-training Y Zhou, Y Wang, P Tang, S Bai, W Shen, E Fishman, A Yuille 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 121-140, 2019 | 192* | 2019 |
Object detection in videos by high quality object linking P Tang, C Wang, X Wang, W Liu, W Zeng, J Wang IEEE transactions on pattern analysis and machine intelligence 42 (5), 1272-1278, 2019 | 123* | 2019 |
Shape-Texture Debiased Neural Network Training Y Li, Q Yu, M Tan, J Mei, P Tang, W Shen, A Yuille, C Xie International Conference on Learning Representations (ICLR), 2021 | 116 | 2021 |
Re-ranking via metric fusion for object retrieval and person re-identification S Bai, P Tang, PHS Torr, LJ Latecki Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 112 | 2019 |
Proposal learning for semi-supervised object detection P Tang, C Ramaiah, Y Wang, R Xu, C Xiong Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 102 | 2021 |
Deep FisherNet for image classification P Tang, X Wang, B Shi, X Bai, W Liu, Z Tu IEEE transactions on neural networks and learning systems 30 (7), 2244-2250, 2018 | 96* | 2018 |
Deep patch learning for weakly supervised object classification and discovery P Tang, X Wang, Z Huang, X Bai, W Liu Pattern Recognition 71, 446-459, 2017 | 79 | 2017 |
Look closer to ground better: Weakly-supervised temporal grounding of sentence in video Z Chen, L Ma, W Luo, P Tang, KYK Wong arXiv preprint arXiv:2001.09308, 2020 | 75 | 2020 |
Robustness of object recognition under extreme occlusion in humans and computational models H Zhu, P Tang, J Park, S Park, A Yuille Proceedings of the Annual Conference of the Cognitive Science Society, 2019 | 51 | 2019 |
Learning multi-instance deep discriminative patterns for image classification P Tang, X Wang, B Feng, W Liu IEEE transactions on image processing 26 (7), 3385-3396, 2016 | 51 | 2016 |
Rethinking ReLU to Train Better CNNs G Zhao, Z Zhang, H Guan, P Tang, J Wang 2018 24th International Conference on Pattern Recognition (ICPR), 603-608, 2018 | 45* | 2018 |
Training multi-organ segmentation networks with sample selection by relaxed upper confident bound Y Wang, Y Zhou, P Tang, W Shen, EK Fishman, AL Yuille Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 31 | 2018 |
Docformerv2: Local features for document understanding S Appalaraju, P Tang, Q Dong, N Sankaran, Y Zhou, R Manmatha Proceedings of the AAAI Conference on Artificial Intelligence 38 (2), 709-718, 2024 | 29 | 2024 |
Learning inductive attention guidance for partially supervised pancreatic ductal adenocarcinoma prediction Y Wang, P Tang, Y Zhou, W Shen, EK Fishman, AL Yuille IEEE transactions on medical imaging 40 (10), 2723-2735, 2021 | 28 | 2021 |
Bag similarity network for deep multi-instance learning X Wang, Y Yan, P Tang, W Liu, X Guo Information Sciences 504, 578-588, 2019 | 21 | 2019 |
Learning extremely shared middle-level image representation for scene classification P Tang, J Zhang, X Wang, B Feng, F Roli, W Liu Knowledge and Information Systems 52, 509-530, 2017 | 13 | 2017 |