Yu Liu

General Manager & Senior Director, SenseTime PI, Shanghai AI Lab Industrial doctoral supervisor, SJTU liuyuisanai@gmail.com Google Scholar

News

• Job positions and PhD program are open for talents interested in AIGC, super HUGE model for NLP and CV and Game AI.

• [2023] Our OpenDILab achieves 10,000+ stars on GitHub!

• [2023] My team have 4 papers published on ICLR/AAAI in 2023

• [2023] My team won the championship of CARLA Autonomous Driving Challenge

• [2022] My team have 9 papers published on ECCV/CoRL/NeurIPS/AAAI in 2022

• [2022] We release DI-Star, an implementation of AlphaStar in pyTorch, beating pro players with 6000+ MMR.

• [2021] My team won the best paper of ICCV21 MFR workshop

• [2021] My team won 3 championships of ICCV21 The Masked Face Recognition Challenge

• [2021] We release OpenDILab, an open source decision intelligence platform

• [2020] 5 papers with 1 oral got published on CVPR/ECCV 2020

• [2020] My team won 2 championships of ActivityNet on the Spatio-temporal Action Localization (AVA) track and the Trimmed Activity Recognition (Kinetics) track

• [2020] My team won the championship of NIST FRVT 1:N, a 12-million-level commercial facial recognition benchmark held by US government.

Read more

• [2019] 7 papers with 4 oral presentations published on ICCV/CVPR/AAAI in 2019

• [2019] I won 4 champions in 4 ICCV AI challenges:MMIT (solutions), OpenImage Instance Segmentation Challenge (solutions), OpenImage Object Detection Challenge (solutions), LFR 2019 (model and report)

• [2019] I was granted the Google PhD Fellowship 2019.

• [2018] 4 papers published by CVPR/ECCV/IJCV/AAAI in 2018.

• [2017] 6 papers published on CVPR/ICCV/NIPS/AAAI/T-PAMI in 2017.

• [2016] We win the 1st place in ECCV-MOT16 Challenge! code

• [2016] We win the 1st place in ImageNet Challenge 2016! code

About me

I am currently the Senior Director of Research in SenseTime Group, and the GM of ADG Business Unit. Previously I obtain my PhD from MMLab, CUHK, supervised by Prof. Xiaogang Wang.
When I was young, I devoted myself to various cutting-edge AI research problems and published dozens of papers in top-tier conferences. However, with a deeper understanding of technology, I am now more focused on tackling problems that can truly advance the field and make AI serve all of humanity. Therefore, since 2020, I have not been concerned with the quantity of "research papers", and have instead formed a team of over 100 researchers and product developers. With over 4,000 GPUs at our disposal, we are committed to creating top-notch technology and ChatGPT-like products based on super HUGE NLP and CV models that can serve the public. Contact me if you are interested.

Working Experience

• GM & Senior Director of Research, SenseTime Group. (since Oct. 2019)
  

• (part-time) PI at Shanghai AI Lab. (since Jan. 2020)
  

• Research internship at Google Research, Seattle and Microsoft Research when I was a student.
  

Publications

• ReasonNet: End-to-End Driving with Temporal and Global Reasoning
  Hao Shao, Letian Wang, Ruobing Chen, Steven L. Waslander, Hongsheng Li, Yu Liu⁺
  (CARLA 2022 Champion) 2023 CVPR

• MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers
  Jihao Liu, Xin Huang, Jinliang Zheng, Yu Liu⁺, Hongsheng Li
  2023 CVPR

• GoBigger: A Scalable Platform for Cooperative-Competitive Multi-Agent Interactive Simulation, Project, Challenge
  Ming Zhang, Shenghan Zhang, Zhenjie Yang, Lekai Chen, Jinliang Zheng, Chao Yang, Chuming Li, Hang Zhou, Yazhe Niu, Yu Liu⁺
  2023 ICLR

• Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency
  Chuming Li, Jie Liu, Yinmin Zhang, Yuhong Wei, Yazhe Niu, Yaodong Yang, Yu Liu⁺, Wanli Ouyang
  2023 AAAI

• Large-batch Optimization for Dense Visual Predictions, Code
  Zeyue Xue, Jianming Liang, Guanglu Song, Zhuofan Zong, Liang Chen, Yu Liu⁺, Ping Luo⁺
  2022 NeurIPS

• Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer
  Hao Shao, Letian Wang, Ruobing Chen, Hongsheng Li, Yu Liu⁺
  2022 CoRL

• UniNet: Unified Architecture Search with Convolution, Transformer, and MLP
  Jihao Liu, Xin Huang, Guanglu Song, Hongsheng Li⁺, Yu Liu⁺
  2022 ECCV

• Self-slimmed Vision Transformer
  Zhuofan Zong, Kunchang Li, Guanglu Song, Yali Wang, Yu Qiao, Biao Leng, Yu Liu⁺
  2022 ECCV

• TokenMix: Rethinking Image Mixing for Data Augmentation in Vision Transformers
  Jihao Liu, Boxiao Liu, Hang Zhou, Hongsheng Li⁺, Yu Liu⁺
  2022 ECCV

• Unifying Visual Perception by Dispersible Points Learning
  Jianming Liang, Guanglu Song, Biao Leng, Yu Liu⁺
  2022 ECCV

• Towards Robust Face Recognition with Comprehensive Search
  Manyuan Zhang, Guanglu Song, Yu Liu⁺, Hongsheng Li
  2022 ECCV

• Rethinking Robust Representation Learning Under Fine-grained Noisy Faces
  Bingqi Ma, Guanglu Song, Boxiao Liu, Yu Liu⁺
  2022 ECCV

• UniFormer: Unified Transformer for Efficient Spatial-Temporal Representation Learning, Code
  Kunchang Li, Yali Wang, Peng Gao, Guanglu Song, Yu Liu, Hongsheng Li, Yu Qiao
  2022 ICLR

• Switchable K-class Hyperplanes for Noise-robust Representation Learning
  Boxiao Liu, Guanglu Song, Manyuan Zhang, Haihang You, Yu Liu⁺
  2021 ICCV

• Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization
  Junting Pan, Siyu Chen, Mike Zheng Shou, Yu Liu, Jing Shao, Hongsheng Li
  2021 CVPR

• Discriminability Distillation in Group Representation Learning
  Manyuan Zhang, Guanglu Song, Hang Zhou, Yu Liu⁺
  2020 ECCV

• Learning Where to Focus for Efficient Video Object Detection
  Zhengkai Jiang, Yu Liu⁺, Ceyuan Yang, Jihao Liu, Gao Peng, Qian Zhang, Shiming Xiang, Chunhong Pan
  2020 ECCV

• Search to Distill: Pearls are Everywhere but not the Eyes
  Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang
  (Oral) 2020 CVPR

• Revisiting the Sibling Head in Object Detector
  Guanglu Song, Yu Liu⁺, Xiaogang Wang
  (OpenImage 2019 Champion) 2020 CVPR

• Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images
  Hang Zhou, Jihao Liu, Ziwei Liu, Yu Liu⁺, Xiaogang Wang
  2020 CVPR

• KPNet: Towards Minimal Face Detector
  Guanglu Song, Yu Liu⁺, Yuhang Zang, Xiaogang Wang, Biao Leng, Qingsheng Yuan
  (Oral) 2020 AAAI

• Temporal Interlacing Network
  Hao Shao, Shengju Qian, Yu Liu⁺
  2020 AAAI

• Differentiable Kernel Evolution
  Yu Liu, Jihao Liu, Ailing Zeng, Xiaogang Wang
  2019 IEEE ICCV

• Towards Flops-constrained Face Recognition, Code
  Yu Liu*, Guanglu Song*, Manyuan Zhang*, Jihao Liu*, Yucong Zhou, Junjie Yan
  (Top-1 Solution) 2019 ICCV Lightweight Face Recognition Challenge & Workshop

• Gradient Harmonized Single-stage Detector,Code
  Buyu Li*, Yu Liu*, Xiaogang Wang
  (Oral) 2019 AAAI

• Conditional Adversarial Generative Flow for Controllable Image Synthesis
  Rui Liu, Yu Liu, Xinyu Gong, Xiaogang Wang, Hongsheng Li
  2019 CVPR

• Exploring Disentangled Feature Representation Beyond Face Identification
  Yu Liu, Fangyin Wei, Jing Shao, Lv Sheng, Junjie Yan, Xiaogang Wang
  2018 CVPR

• Transductive Centroid Projection for Semi-supervised Large-scale Recognition
  Yu Liu, Guanglu Song, Jing Shao, Xiao Jin, Xiaogang Wang
  2018 ECCV

• Rethinking Feature Discrimination and Polymerization for Large-scale Recognition
  Yu Liu, Hongyang Li, Xiaogang Wang
  2017 NIPS deep learning workshop

• Recurrent Scale Approximation for Object Detection in CNN, Code
  Yu Liu, Hongyang Li, Junjie Yan et al.
  2017 IEEE ICCV

• Beyond Trade-off: Accelerate FCN-based Face Detector with Higher Accuracy
  Guanglu Song*, Yu Liu*, Ming Jiang, Yujie Wang, Junjie Yan, Biao Leng
  2018 CVPR

• Quality Aware Network for Set to Set Recognition, Code
  Yu Liu, Junjie Yan, Wanli Ouyang
  2017 CVPR

• Knowledge Distillation via Route Constrained Optimization
  Xiao Jin, Baoyun Peng, Yichao Wu, Yu Liu, Jiaheng Liu, Ding Liang, Junjie Yan, Xiaolin Hu
  (Oral) 2019 IEEE ICCV

• Correlation Congruence for Knowledge Distillation
  Baoyun Peng, Xiao Jin, Jiaheng Liu, Shunfeng Zhou, Yichao Wu, Yu Liu, Dongsheng Li, Zhaoning Zhang
  2019 IEEE ICCV

• Talking Face Generation by Adversarially Disentangled Audio-Visual Representation, Code
  Hang Zhou, Yu Liu, Ziwei Liu, Ping Luo, Xiaogang Wang
  (Oral) 2019 AAAI

• Zoom Out-and-In Network with Map Attention Decision for Region Proposal and Object Detection, Code
  Hongyang Li, Yu Liu, W Ouyang, X Wang
  2018 IJCV

• Region-based Quality Estimation Network for Large-Scale Person Re-identification
  Guanglu Song, Biao Leng, Yu Liu, Congrui Hetang, Shaofan Cai
  2018 AAAI

• Learning Deep Features via Congenerous Cosine Loss for Person Recognition, Code
  Yu Liu, Hongyang Li, Xiaogang Wang
  arxiv:1702.06890, 2017

• Scale-Aware Face Detection
  Zekun Hao, Yu Liu, Hongwei Qin, Junjie Yan
  2017 CVPR

• POI: Multiple Object Tracking with High Performance Detection and Appearance Feature
  F Yu, W Li, Q Li, Y Liu, X Shi, J Yan
  (Top-1 Solution) 2016 ECCV workshop

• Crafting GBD-Net for Object Detection
  X Zeng, W Ouyang, J Yan, H Li, T Xiao, K Wang, Y Liu, Y Zhou, B Yang, ...
  T-PAMI

• 3D object understanding with 3D Convolutional Neural Networks
  B Leng, Y Liu, K Yu, X Zhang, Z Xiong
  Information Sciences 366, 188-201, 2016

Projects & Datasets

GitHub

• OpenDILab, a generalized Decision Intelligence engine.

• X-Temporal, Easily implement SOTA video understanding methods with PyTorch on multiple machines and GPUs

• CaffeMex v2.3, a multi-GPU & memory-reduced MAT-Caffe on LINUX and WINDOWS

• Labeled Pedestrains in the Wild ，a large scale pedestrain re-identification benchmark

Yu Liu