Zhiwei Deng

I am currently a postdoctoral researcher at Princeton University, Computer Science Department.

I did my PhD at Simon Fraser University at VML lab advised by Professor Greg Mori. Previously, I completed my MSc. degree in the same university and received the BEng. degree from Beijing University of Posts and Telecomms.

I am interested in building (1) general purpose reasoning machines, e.g. with graphs, image or language; (2) autonomous navigation agents and beyond; (3) generative models on images, graphs or 3D data.

Email  /  Google Scholar  /  Github

profile photo

Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation
Zhiwei Deng, Karthik Narasimhan, Olga Russakovsky
NeurIPS 2020
code  /  poster  /  Princeton Robotics Seminar

BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps
Wang Zhu*, Hexiang Hu*, Jiacheng Chen, Zhiwei Deng, Vihan Jain, Eugene Ie, Fei Sha
ACL 2020  

Take the Scenic Route: Improving Generalization in Vision-and-Language Navigation
Felix Yu, Zhiwei Deng, Karthik Narasimhan, Olga Russakovsky
Visual Learning with Limited Labels Workshop, CVPR 2020   (Oral)
arxiv / code

Continuous Graph Flow
Zhiwei Deng*, Megha Nawhal*, Lili Meng and Greg Mori.
ICML 2020 - Workshop on Graph Representation Learning and Beyond 2020  
code  /  webpage

Policy Message Passing: Modeling Trajectories for Probabilistic Graph Inference
Zhiwei Deng, Xingguo Li and Greg Mori.
Arxiv 2019  

Talking With Hands 16.2M: A Large-Scale Dataset of Synchronized Body-Finger Motion and Audio for Conversational Motion Analysis and Synthesis.
Gilwoo Lee, Zhiwei Deng, Shugao Ma, Takaaki Shiratori, Siddhartha S. Srinivasa and Yaser Sheikh.
ICCV 2019  

Learning Structured Inference Neural Networks with Label Relations.
Nelson Nauata, Hexiang Hu, Guang-tong Zhou, Zhiwei Deng, Zicheng Liao and Greg Mori.
PAMI 2019

Probabilistic Neural Programmed Networks for Scene Generation.
Zhiwei Deng, Jiacheng Chen, Yifang Fu and Greg Mori.
Neural Information Processing Systems(NeurIPS) 2018 ((Spotlight), 3.5% acceptance rate)
code  /  poster

Sparsely Aggregated Convolutional Networks.
Ligeng Zhu, Ruizhi Deng, Michael Maire, Zhiwei Deng and Greg Mori.
ECCV 2018

Factorized Variational Autoencoders for Modeling Audience Reactions to Movies.
Zhiwei Deng, Rajitha Navarathna, Peter Carr, Stephan Mandt, Yisong Yue, Iain Matthews and Greg Mori.
CVPR 2017
(Press Coverage PHYS.ORG | Caltech News | EurekAlert!)

Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition.
Zhiwei Deng, Arash Vahdat, Hexiang Hu and Greg Mori.
CVPR 2016
arxiv  /  Webpage  /  Extended Collective Activity Dataset: train-test split

A Hierarchical Deep Temporal Model for Group Activity Recognition.
Moustafa Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori.
CVPR 2016

Deep Structured Models For Group Activity Recognition.
Zhiwei Deng, Mengyao Zhai, Lei Chen, Yuhao Liu, Srikanth Muralidharan, Mehrsan Roshtkhari, and Greg Mori.
BMVC 2015 (oral, acceptance rate=7%)

Invited talks

  • Princeton University, PIXL talk, 2019.
  • University of California, Berkeley, EECS, 2019.
  • Vector Institute's Endless Summer School, 2019.


  • Senior Program Committee for: IJCAI 2021
  • Reviewers for: NIPS 2017-2020, CVPR 2017-2020, ICML 2018-2020, ECCV 2018-2020, NIPS 2018-2020, ACL 2020, EMNLP 2020, ICLR 2020, PAMI

Thanks to Jon Barron for this nice website template.