| Uniter: Universal image-text representation learning YC Chen, L Li, L Yu, A El Kholy, F Ahmed, Z Gan, Y Cheng, J Liu European Conference on Computer Vision, 104-120, 2020 | 2807* | 2020 |
| Attngan: Fine-grained text to image generation with attentional generative adversarial networks T Xu, P Zhang, Q Huang, H Zhang, Z Gan, X Huang, X He Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 2237 | 2018 |
| Variational Autoencoder for Deep Learning of Images, Labels and Captions Y Pu, Z Gan, R Henao, X Yuan, C Li, A Stevens, L Carin NIPS, 2016 | 1056 | 2016 |
| Patient knowledge distillation for bert model compression S Sun, Y Cheng, Z Gan, J Liu arXiv preprint arXiv:1908.09355, 2019 | 944 | 2019 |
| Less is more: Clipbert for video-and-language learning via sparse sampling J Lei, L Li, L Zhou, Z Gan, TL Berg, M Bansal, J Liu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 748 | 2021 |
| Git: A generative image-to-text transformer for vision and language J Wang, Z Yang, X Hu, L Li, K Lin, Z Gan, Z Liu, C Liu, L Wang arXiv preprint arXiv:2205.14100, 2022 | 591 | 2022 |
| Hero: Hierarchical encoder for video+ language omni-representation pre-training L Li, YC Chen, Y Cheng, Z Gan, L Yu, J Liu arXiv preprint arXiv:2005.00200, 2020 | 566 | 2020 |
| Semantic compositional networks for visual captioning Z Gan, C Gan, X He, Y Pu, K Tran, J Gao, L Carin, L Deng Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 555 | 2017 |
| Freelb: Enhanced adversarial training for natural language understanding C Zhu, Y Cheng, Z Gan, S Sun, T Goldstein, J Liu International Conference on Learning Representations, 2020 | 548 | 2020 |
| Large-scale adversarial training for vision-and-language representation learning Z Gan, YC Chen, L Li, C Zhu, Y Cheng, J Liu Advances in Neural Information Processing Systems 33, 6616-6628, 2020 | 543 | 2020 |
| Adversarial feature matching for text generation Y Zhang, Z Gan, K Fan, Z Chen, R Henao, D Shen, L Carin International conference on machine learning, 4006-4015, 2017 | 483 | 2017 |
| An empirical study of gpt-3 for few-shot knowledge-based vqa Z Yang, Z Gan, J Wang, X Hu, Y Lu, Z Liu, L Wang Proceedings of the AAAI conference on artificial intelligence 36 (3), 3081-3089, 2022 | 439 | 2022 |
| Relation-aware graph attention network for visual question answering L Li, Z Gan, Y Cheng, J Liu Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 438 | 2019 |
| Club: A contrastive log-ratio upper bound of mutual information P Cheng, W Hao, S Dai, J Liu, Z Gan, L Carin International conference on machine learning, 1779-1788, 2020 | 425 | 2020 |
| An empirical study of training end-to-end vision-and-language transformers ZY Dou, Y Xu, Z Gan, J Wang, S Wang, L Wang, C Zhu, P Zhang, L Yuan, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 413 | 2022 |
| Stylenet: Generating attractive visual captions with styles C Gan, Z Gan, X He, J Gao, L Deng Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 391 | 2017 |
| Discourse-aware neural extractive text summarization J Xu, Z Gan, Y Cheng, J Liu arXiv preprint arXiv:1910.14142, 2019 | 365 | 2019 |
| Scaling up vision-language pre-training for image captioning X Hu, Z Gan, J Wang, Z Yang, Z Liu, Y Lu, L Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 323 | 2022 |
| Generating informative and diverse conversational responses via adversarial information maximization Y Zhang, M Galley, J Gao, Z Gan, X Li, C Brockett, B Dolan Advances in Neural Information Processing Systems 31, 2018 | 321 | 2018 |
| Swinbert: End-to-end transformers with sparse attention for video captioning K Lin, L Li, CC Lin, F Ahmed, Z Gan, Z Liu, Y Lu, L Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 311 | 2022 |
Yu ChengThe Chinese University of Hong Kong在 cse.cuhk.edu.hk 的电子邮件经过验证