| Transductive unbiased embedding for zero-shot learning J Song, C Shen, Y Yang, Y Liu, M Song Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 246 | 2018 |
| Data-free adversarial distillation G Fang, J Song, C Shen, X Wang, D Chen, M Song arXiv preprint arXiv:1912.11006, 2019 | 181 | 2019 |
| Amalgamating knowledge towards comprehensive classification C Shen, X Wang, J Song, L Sun, M Song Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3068-3075, 2019 | 104 | 2019 |
| Contrastive model inversion for data-free knowledge distillation G Fang, J Song, X Wang, C Shen, X Wang, M Song arXiv preprint arXiv:2105.08584, 2021 | 99 | 2021 |
| Learning domain adaptive object detection with probabilistic teacher M Chen, W Chen, S Yang, J Song, X Wang, L Zhang, Y Yan, D Qi, ... arXiv preprint arXiv:2206.06293, 2022 | 96 | 2022 |
| Label matching semi-supervised object detection B Chen, W Chen, S Yang, Y Xuan, J Song, D Xie, S Pu, M Song, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 88 | 2022 |
| Up to 100x faster data-free knowledge distillation G Fang, K Mo, X Wang, J Song, S Bei, H Zhang, M Song Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6597-6604, 2022 | 86 | 2022 |
| Spot-adaptive knowledge distillation J Song, Y Chen, J Ye, M Song IEEE Transactions on Image Processing 31, 3359-3370, 2022 | 84 | 2022 |
| Deep model transferability from attribution maps J Song, Y Chen, X Wang, C Shen, M Song Advances in Neural Information Processing Systems 32, 2019 | 71 | 2019 |
| Root-aligned SMILES: a tight representation for chemical reaction prediction Z Zhong, J Song, Z Feng, T Liu, L Jia, S Yao, M Wu, T Hou, M Song Chemical Science 13 (31), 9023-9034, 2022 | 70 | 2022 |
| Customizing student networks from heterogeneous teachers via adaptive knowledge amalgamation C Shen, M Xue, X Wang, J Song, L Sun, M Song Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 64 | 2019 |
| Progressive network grafting for few-shot knowledge distillation C Shen, X Wang, Y Yin, J Song, S Luo, M Song Proceedings of the AAAI Conference on Artificial Intelligence 35 (3), 2541-2549, 2021 | 62 | 2021 |
| Protopformer: Concentrating on prototypical parts in vision transformers for interpretable image recognition M Xue, Q Huang, H Zhang, L Cheng, J Song, M Wu, M Song arXiv preprint arXiv:2208.10431, 2022 | 56 | 2022 |
| Attention diversification for domain generalization R Meng, X Li, W Chen, S Yang, J Song, X Wang, L Zhang, M Song, D Xie, ... European conference on computer vision, 322-340, 2022 | 47 | 2022 |
| Learning with recoverable forgetting J Ye, Y Fu, J Song, X Yang, S Liu, X Jin, M Song, X Wang European Conference on Computer Vision, 87-103, 2022 | 46 | 2022 |
| Meta-attention for vit-backed continual learning M Xue, H Zhang, J Song, M Song Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 46 | 2022 |
| Mosaicking to distill: Knowledge distillation from out-of-domain data G Fang, Y Bao, J Song, X Wang, D Xie, C Shen, M Song Advances in Neural Information Processing Systems 34, 11920-11932, 2021 | 43 | 2021 |
| A survey on explainable reinforcement learning: Concepts, algorithms, challenges Y Qing, S Liu, J Song, H Wang, M Song arXiv preprint arXiv:2211.06665, 2022 | 37 | 2022 |
| Depara: Deep attribution graph for deep knowledge transferability J Song, Y Chen, J Ye, X Wang, C Shen, F Mao, M Song Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 36 | 2020 |
| Selective zero-shot classification with augmented attributes J Song, C Shen, J Lei, AX Zeng, K Ou, D Tao, M Song Proceedings of the European Conference on Computer Vision (ECCV), 468-483, 2018 | 35 | 2018 |
Song, MingliFull Professor of Computer Science, Zhejiang UniversityPatvirtintas el. paštas zju.edu.cn
