| Densely Connected Convolutional Networks G Huang*, Z Liu*, L Maaten, KQ Weinberger, *equal contribution Computer Vision and Pattern Recognition (CVPR), 2017, 2017 | 39318 | 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 | 2363 | 2017 |
| Deep Networks with Stochastic Depth G Huang*, Y Sun*, Z Liu, D Sedra, KQ Weinberger European Conference on Computer Vision (ECCV), 2016, 2016 | 2307 | 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 | 2212 | 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 | 1379 | 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 | 922 | 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 | 705 | 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 | 623 | 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 | 447* | 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 | 438* | 2021 |
| 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 | 135 | 2020 |
| Few Sample Knowledge Distillation for Efficient Network Compression T Li, J Li, Z Liu, C Zhang Computer Vision and Pattern Recognition (CVPR), 2020, 2020 | 127* | 2020 |
| 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 | 85 | 2022 |
| Object detection from scratch with deep supervision Z Shen, Z Liu, J Li, YG Jiang, Y Chen, X Xue Pattern Analysis and Machine Intelligence (PAMI), 2019 | 84 | 2019 |
| Imagebind: One Embedding Space to Bind Them All R Girdhar*, A El-Nouby*, Z Liu, M Singh, KV Alwala, A Joulin, I Misra* Computer Vision and Pattern Recognition (CVPR), 2023, 2023 | 82* | 2023 |
| ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders S Woo, S Debnath, R Hu, X Chen, Z Liu, IS Kweon, S Xie Computer Vision and Pattern Recognition (CVPR), 2023, 2023 | 62 | 2023 |
| 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 | 53* | 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 | 29 | 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 | 15* | 2021 |
| Exploring Simple and Transferable Recognition-Aware Image Processing Z Liu, T Zhou, HJ Wang, Z Shen, B Kang, E Shelhamer, T Darrell Pattern Analysis and Machine Intelligence (PAMI), 2022 | 14 | 2022 |
Gao Huang （黄高）Associate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
