| Densely Connected Convolutional Networks G Huang*, Z Liu*, L Maaten, KQ Weinberger Computer Vision and Pattern Recognition (CVPR), 2017, 2017 | 35397 | 2017 |
| 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 | 2157 | 2017 |
| Deep Networks with Stochastic Depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger European Conference on Computer Vision (ECCV), 2016, 2016 | 2140 | 2016 |
| A ConvNet for the 2020s Z Liu, H Mao, CY Wu, C Feichtenhofer, T Darrell, S Xie Computer Vision and Pattern Recognition (CVPR), 2022, 2022 | 1342 | 2022 |
| Rethinking the Value of Network Pruning Z Liu, M Sun, T Zhou, G Huang, T Darrell International Conference on Learning Representations (ICLR), 2019, 2019 | 1258 | 2019 |
| Snapshot Ensembles: Train 1, Get M for Free G Huang, Y Li, G Pleiss, Z Liu, JE Hopcroft, KQ Weinberger International Conference on Learning Representations (ICLR), 2017, 2017 | 836 | 2017 |
| DSOD: Learning Deeply Supervised Object Detectors from Scratch Z Shen, Z Liu, J Li, YG Jiang, Y Chen, X Xue International Conference on Computer Vision (ICCV), 2017, 2017 | 661 | 2017 |
| Few-shot Object Detection via Feature Reweighting B Kang, Z Liu, X Wang, F Yu, J Feng, T Darrell International Conference on Computer Vision (ICCV), 2019, 2019 | 560 | 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 (ICML), 2020, 2020 | 371* | 2020 |
| Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning Y Chen, Z Liu, H Xu, T Darrell, X Wang International Conference on Computer Vision (ICCV), 2021, 2021 | 362* | 2021 |
| 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 (TPAMI), 2019 | 313 | 2019 |
| Few Sample Knowledge Distillation for Efficient Network Compression T Li, J Li, Z Liu, C Zhang Computer Vision and Pattern Recognition (CVPR), 2020, 2020 | 114* | 2020 |
| MSeg: A Composite Dataset for Multi-domain Semantic Segmentation J Lambert*, Z Liu*, O Sener, J Hayes, V Koltun Computer Vision and Pattern Recognition (CVPR), 2020, 2020 | 112 | 2020 |
| 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 (TPAMI), 2019 | 78 | 2019 |
| Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning Z Shen, Z Liu, Z Liu, M Savvides, T Darrell, E Xing AAAI Conference on Artificial Intelligence (AAAI), 2022, 2022 | 69* | 2022 |
| Regularization Matters in Policy Optimization--An Empirical Study on Continuous Control Z Liu, X Li, B Kang, T Darrell International Conference on Learning Representations (ICLR), 2021, 2021 | 48 | 2021 |
| Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space A Chavan, Z Shen, Z Liu, Z Liu, KT Cheng, E Xing Computer Vision and Pattern Recognition (CVPR), 2022, 2022 | 20 | 2022 |
| ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders S Woo, S Debnath, R Hu, X Chen, Z Liu, IS Kweon, S Xie arXiv preprint arXiv:2301.00808, 2023 | 17 | 2023 |
| Exploring Simple and Transferable Recognition-Aware Image Processing Z Liu, T Zhou, HJ Wang, Z Shen, B Kang, E Shelhamer, T Darrell IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 | 13* | 2022 |
| SensAI: ConvNets Decomposition via Class Parallelism for Fast Inference on Live Data G Wang, Z Liu, B Hsieh, S Zhuang, J Gonzalez, T Darrell, I Stoica Machine Learning and Systems (MLSys), 2021, 2021 | 12* | 2021 |
Gao Huang （黄高）Associate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
