Xihui Liu
About me
I am 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 the broad area of computer vision and deep learning, with special emphasis on multimodal language and vision. and image synthesis and editing.
I was awarded Adobe Research Fellowship 2020, and selected as one of the EECS Rising Stars 2021.
Education
Ph.D, Department of Electronic Engineering / Multimedia Lab (MMLab), The Chinese University of Hong Kong. (2017 to 2021)
Advised by Prof. Xiaogang Wang and Prof. Hongsheng Li.
Bachelor, Department of Electronic Engineering, Tsinghua University. (2013 to 2017)
Working Experience
Publications
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.
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.
|