| Geodesic Flow Kernel for Unsupervised Domain Adaptation B Gong, Y Shi, F Sha, K Grauman CVPR, 2012 | 1918 | 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 | 626 | 2016 |
| Diverse sequential subset selection for supervised video summarization B Gong, WL Chao, K Grauman, F Sha Advances in neural information processing systems 27, 2069-2077, 2014 | 374 | 2014 |
| 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 | 363 | 2016 |
| 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 | 359 | 2013 |
| 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 | 338 | 2017 |
| 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 | 245 | 2019 |
| F. Sha. Connecting the dots with landmarks: Discriminatively learning domain-invariant features for unsupervised domain adaptation B Gong, K Grauman ICML, 2013 | 189 | 2013 |
| 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 | 172 | 2020 |
| 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 | 167 | 2018 |
| Learning Attributes Equals Multi-Source Domain Generalization C Gan, T Yang, B Gong arXiv preprint arXiv:1605.00743 (Accepted to CVPR 2016), 2016 | 166 | 2016 |
| 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 | 150 | 2018 |
| Reshaping visual datasets for domain adaptation B Gong, K Grauman, F Sha Advances in Neural Information Processing Systems 26, 1286-1294, 2013 | 145 | 2013 |
| Automatic facial expression recognition on a single 3D face by exploring shape deformation B Gong, Y Wang, J Liu, X Tang Proceedings of the 17th ACM international conference on Multimedia, 569-572, 2009 | 121 | 2009 |
| 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 | 109 | 2019 |
| Query-Focused Extractive Video Summarization A Sharghi, B Gong, M Shah arXiv preprint arXiv:1607.05177 (Accepted to ECCV 2016), 2016 | 105 | 2016 |
| Webly-supervised video recognition by mutually voting for relevant web images and web video frames C Gan, C Sun, L Duan, B Gong European Conference on Computer Vision, 849-866, 2016 | 89 | 2016 |
| Learning kernels for unsupervised domain adaptation with applications to visual object recognition B Gong, K Grauman, F Sha International Journal of Computer Vision 109 (1), 3-27, 2014 | 87 | 2014 |
| Query-focused video summarization: Dataset, evaluation, and a memory network based approach A Sharghi, JS Laurel, B Gong Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 85 | 2017 |
| Fast Zero-Shot Image Tagging Y Zhang, B Gong, M Shah arXiv preprint arXiv:1605.09759 (Accepted to CVPR 2016), 2016 | 81 | 2016 |
Fei ShaU of Southern CaliforniaVerified email at usc.edu
