Chen Wei

I am a final-year Computer Science Ph.D. student at Johns Hopkins University, where I am fortunate to be advised by Bloomberg Distinguished Professor Alan L. Yuille. I received my B.S. with honors from Peking University. I spent great time at Google DeepMind, FAIR @ Meta.

weichen3012 [at] gmail [dot] com / Google Scholar / Twitter

Research Interest

My research lies at the intersection of machine learning and computer vision, driven by the goal of developing flexible and general-purpose intelligent systems. My research has primarily focused on two critical steps toward this goal, (1) to encode enormously complex raw visual signals to structured representations that are easier to understand and process for machine, and (2) to connect visual representations to higher-order cognition and commonsense reasoning about the world:

Generative Understanding: constructing and learning from generative models of the world.

Vision and Language: connecting visual representations to commonsense knowledge base like large language models to achieve higher-order cognition.

Self-Supervised Learning: discovering natural structures in the raw data to obtain structured representations that are scalable to wide domains in images and videos, and applicable to a variety of tasks.

I am on the job market for 2024! Would love to chat more if you are interested. I am also happy to give talks on my research in related seminars.

News

[12/01/2023] Gave a talk at Cornell Tech, hosted by Prof. Noah Snavely.

[11/01/2023] Check out the cool examples from De-Diffusion Makes Text a Strong Cross-Modal Interface!

[10/31/2023] Gave a talk at MIT Visual Computing Seminar.

[10/27/2023] Gave a talk at The Computational Vision and Learning Lab @ UCLA.

[08/29/2023] I have been selected as one of the EECS Rising Stars 2023.

[07/16/2023] DiffMAE and SMAUG accepted to ICCV 2023.

[04/23/2023] Hiera accepted to ICML 2023 as oral presentation.

[04/06/2023] Excited to release our new work on reformulating Diffusion Models as Masked Autoencoders.

[10/19/2022] Proud to be an ECCV 2022 outstanding reviewer.

[09/07/2022] Passed my Graduate Board Oral exam and now a PhD candidate :)

Publications

	De-Diffusion Makes Text a Strong Cross-Modal Interface Chen Wei, Chenxi Liu, Siyuan Qiao, Zhishuai Zhang, Alan Yuille, Jiahui Yu arXiv , 2023 arXiv / project page
	Instruct2Attack: Language-Guided Semantic Adversarial Attacks Jiang Liu, Chen Wei, Yuxiang Guo, Heng Yu, Alan Yuille, Soheil Feizi, Chun Pong Lau, Rama Chellappa arXiv , 2023 arXiv
	Diffusion Models as Masked Autoencoders Chen Wei, Karttikeya Mangalam, Po-Yao Huang, Yanghao Li, Haoqi Fan, Hu Xu, Huiyu Wang, Cihang Xie, Alan Yuille, Christoph Feichtenhofer ICCV , 2023 arXiv / project page / Marktechpost
	SMAUG: Sparse Masked Autoencoder for Efficient Video-Language Pre-Training Yuanze Lin, Chen Wei, Huiyu Wang, Alan Yuille, Cihang Xie ICCV , 2023 arXiv
	Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles Chaitanya Ryali, Yuan-Ting Hu, Daniel Bolya, Chen Wei, Haoqi Fan, Po-Yao Huang, Vaibhav Aggarwal, Arkabandhu Chowdhury, Omid Poursaeed, Judy Hoffman, Jitendra Malik, Yanghao Li, Christoph Feichtenhofer* ICML , 2023 Oral arXiv / code
	Masked Autoencoders Enable Efficient Knowledge Distillers Yutong Bai, Zeyu Wang, Junfei Xiao, Chen Wei, Huiyu Wang, Alan Yuille, Yuyin Zhou, Cihang Xie CVPR , 2023 arXiv / code
	CP2: Copy-Paste Contrastive Pretraining for Semantic Segmentation Feng Wang, Huiyu Wang, Chen Wei, Alan Yuille, Wei Shen ECCV , 2022 arXiv / code
	In Defense of Image Pre-Training for Spatiotemporal Recognition Xianhang Li, Huiyu Wang, Chen Wei, Jieru Mei, Alan Yuille, Yuyin Zhou, Cihang Xie ECCV , 2022 arXiv / code
	Masked Feature Prediction for Self-Supervised Visual Pre-Training Chen Wei, Haoqi Fan, Saining Xie, Chao-Yuan Wu, Alan Yuille, Christoph Feichtenhofer CVPR , 2022 arXiv / code at pySlowFast Most Influential CVPR 2023 Papers
	iBOT: Image BERT Pre-Training with Online Tokenizer Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, Tao Kong ICLR , 2022 arXiv / code / press Improved and Scaled up to foundation model DINOv2
	CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning Chen Wei, Kihyuk Sohn, Clayton Mellina, Alan Yuille, Fan Yang CVPR , 2021 arXiv / code / poster / video
	CO2: Consistent Contrast for Unsupervised Visual Representation Learning Chen Wei, Huiyu Wang, Wei Shen, Alan Yuille ICLR , 2021 arXiv / Open Review / video
	Iterative Reorganization with Weak Spatial Constraints: Solving Arbitrary Jigsaw Puzzles for Unsupervised Representation Learning Chen Wei, Lingxi Xie, Xutong Ren, Yingda Xia, Chi Su, Jiaying Liu, Qi Tian, Alan Yuille CVPR, 2019 arXiv / code
	Deep Retinex Decomposition for Low-Light Enhancement Chen Wei, Wenjing Wang, Wenhan Yang, Jiaying Liu BMVC, 2018 Oral arXiv / code / project page & dataset Most Cited BMVC Papers Over the Last Five Years
	GLADNet: Low-Light Enhancement Network with Global Awareness Wenjing Wang, Chen Wei, Wenhan Yang, Jiaying Liu FG Workshop, 2018 PDF / code / project page