| Densely Connected Convolutional Networks G Huang*, Z Liu*, L Maaten, KQ Weinberger Computer Vision and Pattern Recognition (CVPR), 2017, 2017 | 13533 | 2017 |
| Deep Networks with Stochastic Depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger European Conference on Computer Vision (ECCV), 2016, 2016 | 1056 | 2016 |
| Learning Efficient Convolutional Networks through Network Slimming Z Liu, J Li, Z Shen, G Huang, S Yan, C Zhang International Conference on Computer Vision (ICCV), 2017, 2017 | 787 | 2017 |
| Rethinking the value of network pruning Z Liu*, M Sun*, T Zhou, G Huang, T Darrell ICLR 2019, 2018 | 380 | 2018 |
| Dsod: Learning deeply supervised object detectors from scratch Z Shen*, Z Liu*, J Li, YG Jiang, Y Chen, X Xue Proceedings of the IEEE International Conference on Computer Vision, 1919-1927, 2017 | 375 | 2017 |
| Snapshot ensembles: Train 1, get m for free G Huang, Y Li, G Pleiss, Z Liu, JE Hopcroft, KQ Weinberger ICLR 2017, 2017 | 368 | 2017 |
| Few-shot object detection via feature reweighting B Kang*, Z Liu*, X Wang, F Yu, J Feng, T Darrell Proceedings of the IEEE International Conference on Computer Vision, 8420-8429, 2019 | 90 | 2019 |
| Densely connected convolutional networks. arXiv 2016 G Huang, Z Liu, L van der Maaten, KQ Weinberger arXiv preprint arXiv:1608.06993 1608, 2016 | 67 | 2016 |
| Densely connected convolutional networks (2016) G Huang, Z Liu, KQ Weinberger, L van der Maaten arXiv preprint arXiv:1608.06993 7, 2016 | 66 | 2016 |
| Convolutional networks with dense connectivity G Huang, Z Liu, G Pleiss, L Van Der Maaten, K Weinberger IEEE transactions on pattern analysis and machine intelligence, 2019 | 54 | 2019 |
| Test-time training with self-supervision for generalization under distribution shifts Y Sun, X Wang, Z Liu, J Miller, A Efros, M Hardt International Conference on Machine Learning, 9229-9248, 2020 | 34* | 2020 |
| A new meta-baseline for few-shot learning Y Chen, X Wang, Z Liu, H Xu, T Darrell arXiv preprint arXiv:2003.04390, 2020 | 29 | 2020 |
| Few sample knowledge distillation for efficient network compression T Li, J Li, Z Liu, C Zhang arXiv preprint arXiv:1812.01839, 2018 | 23* | 2018 |
| Object detection from scratch with deep supervision Z Shen, Z Liu, J Li, YG Jiang, Y Chen, X Xue IEEE transactions on pattern analysis and machine intelligence 42 (2), 398-412, 2019 | 18 | 2019 |
| Regularization matters in policy optimization Z Liu, X Li, B Kang, T Darrell arXiv preprint arXiv:1910.09191, 2019 | 8 | 2019 |
| Rethinking image mixture for unsupervised visual representation learning Z Shen, Z Liu, Z Liu, M Savvides, T Darrell arXiv preprint arXiv:2003.05438, 2020 | 7 | 2020 |
| MSeg: A Composite Dataset for Multi-domain Semantic Segmentation J Lambert*, Z Liu*, O Sener, J Hayes, V Koltun Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 6 | 2020 |
| Transferable recognition-aware image processing Z Liu, T Zhou, HJ Wang, Z Shen, B Kang, E Shelhamer, T Darrell arXiv preprint arXiv:1910.09185, 2019 | 2 | 2019 |
| sensAI: Fast ConvNets Serving on Live Data via Class Parallelism G Wang, Z Liu, S Zhuang, B Hsieh, J Gonzalez, I Stoica MLSys 2021, 2020 | 1 | 2020 |
| Regularization Matters in Policy Optimization--An Empirical Study on Continuous Control Z Liu, X Li, B Kang, T Darrell arXiv preprint arXiv:1910.09191, 2019 | | 2019 |
Gao Huang （黄高）Assistant Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
