Yu Liu

Department head and tech lead in X-Lab SenseTime Research PhD @ Multimedia Lab, CUHK liuyuisanai@gmail.com yuliu@ee.cuhk.edu.hk Google Scholar Resume GitHub

News

• Job positions and PhD program are open for talents interested in deep RL, representation learning and video understanding.

• [2020] 2 papers got accepted on 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] We won the 4th place of the Facebook Deepfake Detection Challenge

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

• [2020.03.26] I graduate as a PhD after 986 passionate days! Cheers!

• [2020] 3 papers with 1 oral got accepted on CVPR 2020

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

• [2019] I'm the champion of ICCV19 Multi-Moments in Time (MIT) Challenge (solutions)

• [2019] I'm the champion of ICCV19 OpenImage Instance Segmentation Challenge (solutions)

• [2019] I'm the champion of ICCV19 OpenImage Object Detection Challenge (solutions)

• [2019] I'm the champion of ICCV19 Lightweight Face Recognition Challenge (model and report)

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

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

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

• [2017.08] I join CUHK mmlab as a PhD student!

• [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 working as a vice research director in SenseTime Research.

I obtain my PhD from Multimedia Lab (MMLab), the Chinese University of Hong Kong in 2020, supervised by Prof. Xiaogang Wang. Before that I received my bachelor degree in 2016 with best bachelor thesis award. I'm the only awardee of Google PhD Fellowship 2019 in the Greater China area.

My research interests include: Artificial General Intelligence, Deep RL and neural network understanding under billions of data. Previously I was also proficient in basic computer vision topics (detection, classification, recognition, generation, synthesis and video understanding).

In recent years I am a reviewer for CVPR, ICCV, NeurIPS, ICLR, AAAI, IJCAI, T-PAMI, IJCV, TCSVT, TIP, PRCV.

Working Experience

• Senior Researcher (vice director) at SenseTime Research. (since Jan 2020)
  Departments head and tech lead in X-Lab. Leading 2 R&D departments, one for AI decision (RL/system) with its applications (like game AI), and the other one for advanced machine learning (Auto ML/neural network understanding/ optimization for huge models).

• Research intern at Google Research, Seattle. (Jun 2019 to Oct 2019)
  Worked on neural network understanding and NAS with Research Scientists Xuhui Jia, Mingxing Tan and Raviteja Vemulapalli.

• Research intern & part-time researcher consultant at SenseTime Research. (Jan 2016 to Jan 2019)
  Worked on large-scale face analysis (detection, recognition, synthesis), generative model and neural network miniaturizing.

• Research intern at Microsoft Research (Asia), Visual Computing Group. (2015 to 2016)
  Worked on object detection and recognition with Dr. Dong Chen.

Publications

• Discriminability Distillation in Group Representation Learning
  Manyuan Zhang, Guanglu Song, Hang Zhou, Yu Liu⁺
  2020 European Conference on Computer Vision (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 European Conference on Computer Vision (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 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

• Revisiting the Sibling Head in Object Detector
  Guanglu Song, Yu Liu⁺, Xiaogang Wang
  (OpenImage 2019 Champion) 2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

• Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images
  Hang Zhou, Jihao Liu, Ziwei Liu, Yu Liu⁺, Xiaogang Wang
  2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

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

• Temporal Interlacing Network
  Hao Shao, Shengju Qian, Yu Liu⁺
  2020 AAAI Conference on Artificial Intelligence (AAAI)

• Differentiable Kernel Evolution
  Yu Liu, Jihao Liu, Ailing Zeng, Xiaogang Wang
  2019 IEEE International Conference on Computer Vision (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 Conference on Artificial Intelligence (AAAI)

• Conditional Adversarial Generative Flow for Controllable Image Synthesis
  Rui Liu, Yu Liu, Xinyu Gong, Xiaogang Wang, Hongsheng Li
  2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

• Exploring Disentangled Feature Representation Beyond Face Identification
  Yu Liu, Fangyin Wei, Jing Shao, Lv Sheng, Junjie Yan, Xiaogang Wang
  2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

• Transductive Centroid Projection for Semi-supervised Large-scale Recognition
  Yu Liu, Guanglu Song, Jing Shao, Xiao Jin, Xiaogang Wang
  2018 European Conference on Computer Vision (ECCV)

• Rethinking Feature Discrimination and Polymerization for Large-scale Recognition
  Yu Liu, Hongyang Li, Xiaogang Wang
  2017 Conference on Neural Information Processing Systems (NIPS) deep learning workshop

• Recurrent Scale Approximation for Object Detection in CNN, Code
  Yu Liu, Hongyang Li, Junjie Yan et al.
  2017 IEEE International Conference on Computer Vision (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 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

• Quality Aware Network for Set to Set Recognition, Code
  Yu Liu, Junjie Yan, Wanli Ouyang
  2017 IEEE Conference on Computer Vision and Pattern Recognition (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 International Conference on Computer Vision (ICCV)

• Correlation Congruence for Knowledge Distillation
  Baoyun Peng, Xiao Jin, Jiaheng Liu, Shunfeng Zhou, Yichao Wu, Yu Liu, Dongsheng Li, Zhaoning Zhang
  2019 IEEE International Conference on Computer Vision (ICCV)

• Talking Face Generation by Adversarially Disentangled Audio-Visual Representation, Code
  Hang Zhou, Yu Liu, Ziwei Liu, Ping Luo, Xiaogang Wang
  (Oral) 2019 AAAI Conference on Artificial Intelligence (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 International Journal of Computer Vision (IJCV)

• Region-based Quality Estimation Network for Large-Scale Person Re-identification
  Guanglu Song, Biao Leng, Yu Liu, Congrui Hetang, Shaofan Cai<
  2018 AAAI Conference on Artificial Intelligence (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 IEEE Conference on Computer Vision and Pattern Recognition (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 European Conference on Computer Vision (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, ...
  IEEE Transactions on Pattern Analysis and Machine Intelligence (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

• 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