| 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 Proceedings of the 36th International Conference on Machine Learning, 2019 | 214 | 2019 |
| Stnet: Local and global spatial-temporal modeling for action recognition D He, Z Zhou, C Gan, F Li, X Liu, Y Li, L Wang, S Wen Proceedings of the AAAI conference on artificial intelligence 33 (01), 8401-8408, 2019 | 125 | 2019 |
| MoViNets: Mobile Video Networks for Efficient Video Recognition D Kondratyuk, L Yuan, Y Li, L Zhang, M Tan, M Brown, B Gong CVPR 2021, 2021 | 124 | 2021 |
| Transferring robustness for graph neural network against poisoning attacks X Tang, Y Li, Y Sun, H Yao, P Mitra, S Wang Proceedings of the 13th international conference on web search and data …, 2020 | 122* | 2020 |
| Vqs: Linking segmentations to questions and answers for supervised attention in vqa and question-focused semantic segmentation C Gan, Y Li, H Li, C Sun, B Gong Proceedings of the IEEE international conference on computer vision, 1811-1820, 2017 | 117 | 2017 |
| Detecting anomaly in big data system logs using convolutional neural network S Lu, X Wei, Y Li, L Wang 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th …, 2018 | 112 | 2018 |
| Multimodal keyless attention fusion for video classification X Long, C Gan, G Melo, X Liu, Y Li, F Li, S Wen Proceedings of the aaai conference on artificial intelligence 32 (1), 2018 | 109 | 2018 |
| Depthwise convolution is all you need for learning multiple visual domains Y Guo, Y Li, R Feris, L Wang, T Rosing Proceedings of the AAAI Conference on Artificial Intelligence, 2019 | 98 | 2019 |
| Temporal modeling approaches for large-scale youtube-8m video understanding F Li, C Gan, X Liu, Y Bian, X Long, Y Li, Z Li, J Zhou, S Wen arXiv preprint arXiv:1707.04555, 2017 | 63 | 2017 |
| Revisiting the effectiveness of off-the-shelf temporal modeling approaches for large-scale video classification Y Bian, C Gan, X Liu, F Li, X Long, Y Li, H Qi, J Zhou, S Wen, Y Lin arXiv preprint arXiv:1708.03805, 2017 | 57 | 2017 |
| Improving Object Detection with Selective Self-supervised Self-training Y Li, D Huang, D Qin, L Wang, B Gong ECCV 2020, 2020 | 51 | 2020 |
| Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation from a Blackbox Model D Wang, Y Li, L Wang, B Gong CVPR 2020, 2020 | 44 | 2020 |
| BachGAN: High-Resolution Image Synthesis from Salient Object Layout Y Li, Y Cheng, Z Gan, L Yu, L Wang, J Liu CVPR 2020, arXiv: 2003.11690, 2020 | 38 | 2020 |
| How local is the local diversity? reinforcing sequential determinantal point processes with dynamic ground sets for supervised video summarization Y Li, L Wang, T Yang, B Gong Proceedings of the European Conference on Computer Vision (ECCV), 151-167, 2018 | 37 | 2018 |
| Joint modeling of dense and incomplete trajectories for citywide traffic volume inference X Tang, B Gong, Y Yu, H Yao, Y Li, H Xie, X Wang The World Wide Web Conference, 1806-1817, 2019 | 36 | 2019 |
| On Model Calibration for Long-Tailed Object Detection and Instance Segmentation TY Pan, C Zhang, Y Li, H Hu, D Xuan, S Changpinyo, B Gong, WL Chao 2021 Conference on Neural Information Processing Systems, 2021 | 26 | 2021 |
| AdaFilter: Adaptive Filter Fine-tuning for Deep Transfer Learning Y Guo, Y Li, L Wang, T Rosing Proceedings of the AAAI Conference on Artificial Intelligence, 2020 | 25 | 2020 |
| MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection C Zhang, TY Pan, Y Li, H Hu, D Xuan, S Changpinyo, B Gong, WL Chao 2021 International Conference on Computer Vision, 2021 | 21 | 2021 |
| Ranking Neural Checkpoints Y Li, X Jia, R Sang, Y Zhu, B Green, L Wang, B Gong CVPR 2021, 2020 | 17 | 2020 |
| Subject-driven text-to-image generation via apprenticeship learning W Chen, H Hu, Y Li, N Rui, X Jia, MW Chang, WW Cohen arXiv preprint arXiv:2304.00186, 2023 | 5 | 2023 |
Boqing GongResearch Scientist, GoogleEmail verificata su google.com
