Xihui Liu

Assistant Professor, Department of Electrical and Electronic Engineering (EEE) / Institute of Data Science (IDS) The University of Hong Kong xihui.liu.me@gmail.com xihuiliu@eee.hku.hk Google Scholar   CV

About me

I am an Assistant Professor at the Department of Electrical and Electronic Engineering (EEE) and Institute of Data Science (IDS), The University of Hong Kong. Before joining HKU, I was a postdoc Scholar at EECS Department and BAIR at UC Berkeley, advised by Prof. Trevor Darrell. I obtained my Ph.D. degree from Multimedia Lab (MMLab), the Chinese University of Hong Kong, supervised by Prof. Xiaogang Wang and Prof. Hongsheng Li. I received bachelor's degree in Electronic Engineering in Tsinghua University (THU) in 2017. My research interests cover computer vision, machine learning, and artificial intelligence, with special emphasis on multimodal AI, vision and language, open-world recognition, visual synthesis, and generative models. I was awarded Adobe Research Fellowship 2020, MIT EECS Rising Stars 2021, WAIC Rising Stars Award 2022, CVPR 2021 Doctoral Consortium Award, CVPR Outstanding Reviewer, and ICLR Outstanding Reviewer.

I am looking for self-motivated Ph.D. students to join my group in Spring 2023 or Fall 2023. Please drop me an email if you are interested.

Employment and Education

• Assistant Professor, Department of Electrical and Electronic Engineering / Institute of Data Science, The University of Hong Kong. (July 2022 to now)
  

• Postdoc Scholar at Darrell Group / BAIR / EECS Department, UC Berkeley. (August 2021 to July 2022)
  Advised by Prof Trevor Darrell.

• Ph.D, Department of Electronic Engineering / Multimedia Lab (MMLab), The Chinese University of Hong Kong. (August 2017 to July 2021)
  Advised by Prof. Xiaogang Wang and Prof. Hongsheng Li.

• Bachelor, Department of Electronic Engineering, Tsinghua University. (August 2013 to July 2017)
  

Awards

• 2022 WAIC Rising Stars.

• 2021 MIT EECS Rising Stars.

• 2019 Adobe Research Fellowship.

• CVPR 2021 Doctoral Consortium, mentored by Prof. Antonio Torralba.

• ICLR 2021 outstanding reviewer award.

• CVPR 2019 outstanding reviewer award.

• 2017 Tsinghua Outstanding Graduate.

• Champion of ImageNet 2016 Video Object Detection Challenge (as a member of CUVideo team).

Publications

• Point Transformer V2: Grouped Vector Attention and Grid Pooling
  Xiaoyang Wu, Yixing Lao, Li Jiang, Xihui Liu, Hengshuang Zhao
  Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.

• Back to the Source: Diffusion-Driven Test-Time Adaptation
  Jin Gao*, Jialing Zhang*, Xihui Liu, Trevor Darrell, Evan Shelhamer*, Dequan Wang*
  2022.

• MILES: Visual BERT Pre-training with Injected Language Semantics for Video-text Retrieval
  Yuying Ge, Yixiao Ge, Xihui Liu, Alex Jinpeng Wang, Jianping Wu, Ying Shan, Xiaohu Qie, Ping Luo
  European Conference on Computer Vision (ECCV), 2022.

• More Control for Free! Image Synthesis with Semantic Diffusion Guidance [Project Page] [Slides]
  Xihui Liu, Dong Huk Park, Samaneh Azadi, Gong Zhang, Arman Chopikyan, Yuxiao Hu, Humphrey Shi, Anna Rohrbach, Trevor Darrell
  2021.

• BridgeFormer: Bridging Video-text Retrieval with Multiple Choice Questions [Project Page]
  Yuying Ge, Yixiao Ge, Xihui Liu, Dian Li, Ying Shan, Xiaohu Qie, Ping Luo
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

• Benchmark for Compositional Text-to-Image Synthesis
  Dong Huk Park, Samaneh Azadi, Xihui Liu, Trevor Darrell, Anna Rohrbach
  Thirty-third Conference on Neural Information Processing Systems (NeurIPS) Dataset and Benchmark Track, 2021.

• Open-Edit: Open-Domain Image Manipulation with Open-Vocabulary Instructions [Video] [Slides] [Code]
  Xihui Liu, Zhe Lin, Jianming Zhang, Handong Zhao, Quan Tran, Xiaogang Wang, Hongsheng Li
  European Conference on Computer Vision (ECCV), 2020.

• Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis [Code] [Slides]
  Xihui Liu, Guojun Yin, Jing Shao, Xiaogang Wang, Hongsheng Li
  Thirty-third Conference on Neural Information Processing Systems (NeurIPS), 2019.

• Improving Referring Expression Grounding with Cross-modal Attention-guided Erasing [Code]
  Xihui Liu, Zihao Wang, Jing Shao, Xiaogang Wang, Hongsheng Li
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

• Show, Tell and Discriminate: Image Captioning by Self-retrieval with Partially Labeled Data
  Xihui Liu, Hongsheng Li, Jing Shao, Dapeng Chen, Xiaogang Wang
  European Conference on Computer Vision (ECCV), 2018.

• CAMP: Cross-modal Adaptive Message Passing for Text-Image Retrieval [Code]
  Zihao Wang*, Xihui Liu*, Hongsheng Li, Lu Sheng, Junjie Yan, Xiaogang Wang, Jing Shao
  International Conference on Computer Vision (ICCV), 2019.

• Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association
  Dapeng Chen, Hongsheng Li, Xihui Liu, Yantao Shen, Jing Shao, Zejian Yuan, Xiaogang Wang
  European Conference on Computer Vision (ECCV), 2018.

• HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis
  Xihui Liu*, Haiyu Zhao*, Maoqing Tian, Lu Sheng, Jing Shao, Shuai Yi, Junjie Yan, Xiaogang Wang
  International Conference on Computer Vision (ICCV), 2017.

• Localization Guided Learning for Pedestrian Attribute Recognition
  Pengze Liu, Xihui Liu, Junjie Yan, Jing Shao,
  British Machine Vision Conference (BMVC), 2018.

• Orientation invariant feature embedding and spatial temporal regularization for vehicle re-identification
  Zhongdao Wang, Luming Tang, Xihui Liu, Zhuliang Yao, Shuai Yi, Jing Shao, Junjie Yan, Shengjin Wang, Hongsheng Li, Xiaogang Wang
  International Conference on Computer Vision (ICCV), 2017.

• Object Detection in Videos With Tubelet Proposal Networks
  Kai Kang, Hongsheng Li, Tong Xiao, Wanli Ouyang, Junjie Yan, Xihui Liu, Xiaogang Wang
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.

Academic Services

Reviewer of the following conferences and journals:

• Outstanding Reviewer for CVPR 2019 and ICLR 2021.

• CVPR, ICCV, ECCV, NeruIPS, ICML, ICLR, AAAI.

• IJCV, TCSVT, NeuroComputing, TMM.

Research Internships

• Research intern at NVIDIA Research. (2020 summer)
  Worked on video synthesis with Ming-Yu Liu and Ting-Chun Wang.

• Research intern at Adobe Research. (2019 summer)
  Worked on open-vocabulary open-domain image editing with Zhe Lin, Jianming Zhang, Handong Zhao, and Quan Tran.

• Research assistant at Multimedia Lab (MMLab), CUHK. (2016 summer)
  Worked on object detection in videos with Kai Kang, supervised by Prof. Xiaogang Wang.

Teaching Experience

Teaching Assistant of the following courses in The Chinese University of Hong Kong:

• ELEG 5491, Introduction to Deep Learning [Course website], Spring 2019.

• ENGG 5202, Pattern Recognition, Fall 2017, Spring 2020.

• ELEG 5760, Machine Learning for Signal Processing Applications, Fall 2018.

• ENGG 2450A, Probability and Statistics for Engineers, Spring 2018, Fall 2020.

• Summer Tutorial, Potential Inspiration in Electronic Engineering, Summer 2018.

• ENGG 2420B, Complex Analyis and Differential Equations for Engineers, Fall 2019.

• ENGG 2740A, Differential Equations for Engineers, Spring 2021.