| Geodesic Flow Kernel for Unsupervised Domain Adaptation B Gong, Y Shi, F Sha, K Grauman CVPR, 2012 | 2379 | 2012 |
| Synthesized Classifiers for Zero-Shot Learning S Changpinyo, WL Chao, B Gong, F Sha arXiv preprint arXiv:1603.00550 (Accepted to CVPR 2016), 2016 | 820 | 2016 |
| Large-scale long-tailed recognition in an open world Z Liu, Z Miao, X Zhan, J Wang, B Gong, SX Yu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 699 | 2019 |
| Connecting the dots with landmarks: Discriminatively learning domain-invariant features for unsupervised domain adaptation B Gong, K Grauman, F Sha International conference on machine learning, 222-230, 2013 | 569* | 2013 |
| An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild WL Chao, S Changpinyo, B Gong, F Sha arXiv preprint arXiv:1605.04253 (Accepted to ECCV 2016), 2016 | 525 | 2016 |
| Curriculum domain adaptation for semantic segmentation of urban scenes Y Zhang, P David, B Gong Proceedings of the IEEE international conference on computer vision, 2020-2030, 2017 | 472 | 2017 |
| Diverse sequential subset selection for supervised video summarization B Gong, WL Chao, K Grauman, F Sha Advances in neural information processing systems 27, 2014 | 457 | 2014 |
| Adversarial examples improve image recognition C Xie, M Tan, B Gong, J Wang, AL Yuille, QV Le Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 384 | 2020 |
| Spatiotemporal contrastive video representation learning R Qian, T Meng, B Gong, MH Yang, H Wang, S Belongie, Y Cui Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 296 | 2021 |
| Vatt: Transformers for multimodal self-supervised learning from raw video, audio and text H Akbari, L Yuan, R Qian, WH Chuang, SF Chang, Y Cui, B Gong Advances in Neural Information Processing Systems 34, 24206-24221, 2021 | 273 | 2021 |
| Improving the improved training of wasserstein gans: A consistency term and its dual effect X Wei, B Gong, Z Liu, W Lu, L Wang arXiv preprint arXiv:1803.01541, 2018 | 245 | 2018 |
| Polarnet: An improved grid representation for online lidar point clouds semantic segmentation Y Zhang, Z Zhou, P David, X Yue, Z Xi, B Gong, H Foroosh Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 244 | 2020 |
| Domain randomization and pyramid consistency: Simulation-to-real generalization without accessing target domain data X Yue, Y Zhang, S Zhao, A Sangiovanni-Vincentelli, K Keutzer, B Gong Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 218 | 2019 |
| End-to-end learning of motion representation for video understanding L Fan, W Huang, C Gan, S Ermon, B Gong, J Huang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 212 | 2018 |
| Nattack: Learning the distributions of adversarial examples for an improved black-box attack on deep neural networks Y Li, L Li, L Wang, T Zhang, B Gong International Conference on Machine Learning, 3866-3876, 2019 | 205 | 2019 |
| Learning Attributes Equals Multi-Source Domain Generalization C Gan, T Yang, B Gong arXiv preprint arXiv:1605.00743 (Accepted to CVPR 2016), 2016 | 202 | 2016 |
| A fast and accurate one-stage approach to visual grounding Z Yang, B Gong, L Wang, W Huang, D Yu, J Luo Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 175 | 2019 |
| Rethinking class-balanced methods for long-tailed visual recognition from a domain adaptation perspective MA Jamal, M Brown, MH Yang, L Wang, B Gong Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 162 | 2020 |
| Reshaping visual datasets for domain adaptation B Gong, K Grauman, F Sha Advances in Neural Information Processing Systems 26, 2013 | 157 | 2013 |
| When vision transformers outperform resnets without pre-training or strong data augmentations X Chen, CJ Hsieh, B Gong arXiv preprint arXiv:2106.01548, 2021 | 156 | 2021 |
Fei ShaU of Southern CaliforniaEmail verificata su usc.edu
