Liwei Wang

I am an Assistant Professor in Computer Science and Engineering department at The Chinese University of Hong Kong (CUHK). Before coming to HK, I have worked for more than two years as a Senior Researcher in Tencent AI Lab at Bellevue, US.

I got my PhD from Computer Science Department, University of Illinois at Urbana-Champaign, advised by Prof. Svetlana Lazebnik. Here is my Short Bio.

The Language and Vision ("LaVi") Lab I lead in CSE@CUHK do research in Computer Vision, NLP, with the emphasis on the intersection of vision and language.

The goal of LaVi Lab is to build interactive AI systems that can not only understand and recreate the visual world but also communicate like human beings using natural language

, which covers topics of language+vision; embodied AI; multi-modal dialogue; learning from interaction; efficient AI; machine learning methods for Vision and NLP.

LaVi is hiring Phd students, Research Interns and Fulltime Research Engineers in Language +Vision. Candidates with strong research/engineering background are encouraged to apply!

Please drop me an email directly to

lwwang@cse.cuhk.edu.hk

, if you want to work with me.

Email / Google Scholar / To Join LaVi Lab / Publications /

News

2022/07:
Our LaVi team won the annual NLP challenge LIC 2022 (Multi-modal Video Understanding track) hosted by CCF and CIPS, check department news here .
2022/07:
One ECCV paper is accepted
2022/03:
Three papers got accepted to CVPR 2022 including our new work on Language + Vision.
2022/02:
One ACL 2022 long paper from our group on "Probing Pre-trained Models" has bee accepted.
2022/02:
Serving as an Area Chair of ECCV 2022 .
2021/12:
I was invited to give an online talk at Microsoft Vision-and-Language Research Talk Series.
2021/12:
I am teaching CSCI 3320 Fundamentals of Machine Learning at CUHK.
2021/08:
I am teaching CSCI 5640 NLP at CUHK.
2021/08:
Our long paper on Dialog Rewriting was accepted to EMNLP 2021.
2021/08:
I will teach a graduate level new course in CUHK - CSCI 5640 NLP in the coming semester.
2021/08:
Three papers got accepted to ICCV 2021, including one Oral on Language + Vision.
2021/07:
Our collaborated work had won the referit3d CVPR 2021 challenge !
2021/05:
I will teach a new NLP course in CSE at CUHK next semester.
2021/05:
New work on text generation accepted to ACL 2021.
2021/04:
I am joining the Editorial Board of IJCV - top computer vision journal in the world (CCF A journal in AI).
2021/04:
I will serve as the program committee of EMNLP 2021.
2021/04:
CUHK CSE 2022 Fall Early Admission starts! For Phd/Master applicants, please click .
2021/03:
Our work on Logical Reasoning has been accepted by NAACL 2021. Congrats to my intern.
2021/03:
Four CVPR 2021 papers are accepted including one oral paper.
2020/12:
I joined the CSE@CUHK as an assistant professor and started my team working on Language and Vision ("LaVi" Lab).

Research Highlights

My students or interns are indicated by '*'. Click full publication list

	FlowEval: A Consensus-Based Dialogue Evaluation Framework Using Segment Act Flows Jianqiao Zhao, Yanyang Li, Wanyu Du, Yangfeng Ji, Dong Yu, Michael R. Lyu, Liwei Wang* Arxiv, 2022
	Probing Structured Pruning on Multilingual Pre-trained Models: Settings, Algorithms, and Efficiency Yanyang Li, Fuli Luo, Runxin Xu, Songfang Huang, Fei Huang, Liwei Wang* ACL, 2022, long paper
	Multi-View Transformer for 3D Visual Grounding Shijia Huang, Yilun Chen, Jiaya Jia, Liwei Wang* CVPR, 2022 Code
	SAT: 2D Semantics Assisted Training for 3D Visual Grounding Zhengyuan Yang, Songyang Zhang, Liwei Wang, Jiebo Luo ICCV, 2021, Oral Presentation Code
	Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation Liwei Wang, Jing Huang, Yin Li, Kun Xu, Zhengyuan Yang, Dong Yu CVPR, 2021 Code
	Robust Dialogue Utterance Rewriting as Sequence Tagging Jie Hao, Linfeng Song, Liwei Wang, Kun Xu, Zhaopeng Tu, Dong Yu EMNLP, 2021, Code
	Comprehensive Image Captioning via Scene Graph Decomposition Yiwu Zhong, Liwei Wang, Jianshu Chen, Dong Yu, Yin Li ECCV*, 2020 Code
	Improving One-stage Visual Grounding by Recursive Sub-query Construction Zhengyuan Yang, Tianlang Chen, Liwei Wang, Jiebo Luo ECCV, 2020 Code
	MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning Jie Lei, Liwei Wang, Yelong Shen, Dong Yu, Tamara Berg, Mohit Bansal ACL*, 2020 Code
	A Fast and Accurate One-Stage Approach to Visual Grounding Zhengyuan Yang, Boqing Gong, Liwei Wang, Wenbing Huang, Dong Yu, Jiebo Luo ICCV*, 2019, Oral Presentation Code
	Fast, Diverse and Accurate Image Captioning Guided By Part-of-Speech Aditya Deshpande, Jyoti Aneja, Liwei Wang, Alexander Schwing, D. A. Forsyth CVPR, 2019, Oral Presentation
	Learning Two-Branch Neural Networks for Image-Text Matching Tasks Liwei Wang, Yin Li, Jing Huang, Svetlana Lazebnik TPAMI, 2018 Code
	Learning structural motif representations for efficient protein structure search Yang Liu, Qing Ye, Liwei Wang, Jian Peng Bioinformatics, 2018 Code
	Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space Liwei Wang, Alex Schwing, Svetlana Lazebnik NeurIPS, 2017
	Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models Bryan Plummer, Liwei Wang, Chris M. Cervantes, Juan C. Caicedo, Julia Hockenmaier, Svetlana Lazebnik IJCV, 2016 Project
	Learning Deep Structure-Preserving Image-Text Embeddings Liwei Wang, Yin Li, Svetlana Lazebnik CVPR, 2016 Code
	Improving Image-Sentence Embeddings Using Large Weakly Annotated Photo Collections Yunchao Gong, Liwei Wang, Micah Hodosh, Julia Hockenmaier2 Svetlana Lazebnik ECCV, 2014 Code
	Multi-Scale Orderless Pooling of Deep Convolutional Activation Features Yunchao Gong, Liwei Wang, Ruiqi Guo, Svetlana Lazebnik ECCV, 2014 Code
	Learning Sparse Covariance Patterns for Natural Scenes Liwei Wang, Yin Li, Jiaya Jia, Jian Sun, David Wipf, James M. Rehg CVPR, 2012
	Bayesian Face Revisited: A Joint Formulation Dong Chen, Xudong Cao, Liwei Wang, Fang Wen, Jian Sun ECCV, 2012

Former Interns and Mentored Students

I'm extremely thankful for working with these excellent interns and mentored students: Zhengyuan Yang (intern, phd@University of Rochester), Jie Lei (intern, phd@UNC Chapel Hill), Jeff Zhang (intern, student@UIUC), Aishan Liu (intern, now Assistant Professor at Beihang U), Wanyu Du (intern, phd@University of Virginia), Darryl Hanan(intern, phd@UNC Chapel Hill), Yiwu Zhong (intern, phd@University of Wisconsin-Madison), Yifan (intern, phd@UCSD), Yinya (intern, phd@SYSU), Jing Huang (master@UIUC, now@google research)

(Templates adapted from Arun's webpage.)