| Domain agnostic learning with disentangled representations X Peng, Z Huang, X Sun, K Saenko International Conference on Machine Learning, 5102-5112, 2019 | 238 | 2019 |
| Adashare: Learning what to share for efficient deep multi-task learning X Sun, R Panda, R Feris, K Saenko Advances in Neural Information Processing Systems 33, 8728-8740, 2020 | 193 | 2020 |
| Adamml: Adaptive multi-modal learning for efficient video recognition R Panda, CFR Chen, Q Fan, X Sun, K Saenko, A Oliva, R Feris Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 37 | 2021 |
| Dualcoop: Fast adaptation to multi-label recognition with limited annotations X Sun, P Hu, K Saenko Advances in Neural Information Processing Systems 35, 30569-30582, 2022 | 33 | 2022 |
| Dynamic network quantization for efficient video inference X Sun, R Panda, CFR Chen, A Oliva, R Feris, K Saenko Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 30 | 2021 |
| A temporally-aware interpolation network for video frame inpainting X Sun, R Szeto, JJ Corso Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019 | 30* | 2019 |
| Twostreamvan: Improving motion modeling in video generation X Sun, H Xu, K Saenko Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020 | 27* | 2020 |
| Weakly-supervised compositional featureaggregation for few-shot recognition P Hu, X Sun, K Saenko, S Sclaroff arXiv preprint arXiv:1906.04833, 2019 | 24 | 2019 |
| Similarity r-c3d for few-shot temporal activity detection H Xu, B Kang, X Sun, J Feng, K Saenko, T Darrell arXiv preprint arXiv:1812.10000, 2018 | 13 | 2018 |
| Revisiting few-shot activity detection with class similarity control H Xu, X Sun, E Tzeng, A Das, K Saenko, T Darrell arXiv preprint arXiv:2004.00137, 2020 | 11 | 2020 |
| DIME-FM: DIstilling Multimodal and Efficient Foundation Models X Sun, P Zhang, P Zhang, H Shah, K Saenko, X Xia arXiv preprint arXiv:2303.18232, 2023 | 3 | 2023 |
| All at once network quantization via collaborative knowledge transfer X Sun, R Panda, CF Chen, N Wang, B Pan, K Gopalakrishnan, A Oliva, ... ArXiv preprint, 2021 | 2 | 2021 |
| Label Budget Allocation in Multi-Task Learning X Sun, K Sohn, K Saenko, C Mellina, X Bian arXiv preprint arXiv:2308.12949, 2023 | | 2023 |
| Dualcoop++: Fast and effective adaptation to multi-label recognition with limited annotations P Hu, X Sun, S Sclaroff, K Saenko arXiv preprint arXiv:2308.01890, 2023 | | 2023 |
| Dynamic network quantization for efficient video inference R Panda, X Sun, R Chen, RS Feris, E Saenko US Patent App. 17/566,782, 2023 | | 2023 |
| Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths X Sun, R Panda, CF Chen, N Wang, B Pan, K Gopalakrishnan, A Oliva, ... arXiv preprint arXiv:2103.01435, 2021 | | 2021 |
| DIME-FM: Distilling Multimodal and Efficient Foundation Models from CLIP (Supplementary Materials) X Sun, P Zhang, P Zhang, H Shah, K Saenko, X Xia | | |
| AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition (Supplementary Material) R Panda, CFR Chen, Q Fan, X Sun, K Saenko, A Oliva, R Feris | | |
| Dynamic Network Quantization for Efficient Video Inference (Supplementary Material) X Sun, R Panda, CFR Chen, A Oliva, R Feris, K Saenko | | |
| AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning (Supplementary Material) X Sun, R Panda, R Feris, K Saenko | | |
Kate SaenkoBoston UniversityVerified email at bu.edu
