Liang-Chieh (Jay) Chen- Home Page

Liang-Chieh (Jay) Chen
Research Scientist, Apple AI/ML

Email: lcchen at cs dot ucla dot edu

About Me

I am currently a Research Scientist at Apple AI/ML, building cutting-edge visual generative models.

I am widely recognized for my contributions to the DeepLab series (co-developed with George Papandreou): DeepLabv1, DeepLabv2, DeepLabv3, DeepLabv3+. Since December 2014, our introduced atrous convolution (also known as convolution with holes or dilated convolution) has become a foundational technique for dense prediction tasks.

Influential DeepLab derivatives include Auto-DeepLab, Panoptic-DeepLab (winning method of the Mapillary Vistas Panoptic Segmentation track at ICCV 2019, and top performer on Cityscapes leaderboards), Axial-DeepLab, ViP-DeepLab, MaX-DeepLab, and kMaX-DeepLab.

I am also known for my collaborative work on MobileNetv2 and MobileNetv3, which have become standards for efficient neural network design on mobile devices.

Previously, I was a Senior Principal Scientist at Amazon in 2025, and a Research Scientist and Manager at ByteDance Research/TikTok from 2023 to 2025. Prior to that, I spent seven years as a Research Scientist at Google Research in Los Angeles (2016–2023). I received my Ph.D. in Computer Science from the University of California, Los Angeles, in 2015, advised by Alan L. Yuille. I received my M.S. in Electrical and Computer Engineering from the University of Michigan, Ann Arbor.

News

For motivated Ph.D. students looking for internships, feel free to contact me for details. Our team works on fundamental research on computer vision, visual generation, and representation learning.

Activities

Area Chair for ICCV 2019, 2025, CVPR 2020, 2023, 2024, 2025, 2026, ECCV 2020, 2024, NeurIPS 2022, 2024, 2025, ICML 2025.

Action Editor for TMLR.

Reviewer for CVPR, ECCV, ICCV, NeurIPS.

Selected Recent Publications

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers
Sucheng Ren, Qihang Yu, Ju He, Alan Yuille, Liang-Chieh Chen
Technical report
[preprint (arxiv: 2505.14687)] [project website] [code]

ReVision: High-Quality, Low-Cost Video Generation with Explicit 3D Physics Modeling for Complex Motion and Interaction
Qihao Liu, Ju He, Qihang Yu, Liang-Chieh Chen*, Alan Yuille*
(*equal advising)
Technical report
[preprint (arxiv: 2504.21855)] [project website]

COCONut-PanCap: Joint Panoptic Segmentation and Grounded Captions for Fine-Grained Understanding and Generation
Xueqing Deng, Qihang Yu, Ali Athar, Chenglin Yang, Linjie Yang, Xiaojie Jin, Xiaohui Shen, Liang-Chieh Chen
In Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks, San Diego, California, USA, December 2025.
[preprint (arxiv: 2502.02589)] [project website]

Deeply Supervised Flow-Based Generative Models
Inkyu Shin, Chenglin Yang, Liang-Chieh Chen
In International Conference on Computer Vision (ICCV), Honolulu, Hawaii, USA, October 2025.
[preprint (arxiv: 2503.14494)] [project website] [code]

FlowTok: Flowing Seamlessly Across Text and Image Tokens
Ju He, Qihang Yu, Qihao Liu, Liang-Chieh Chen
In International Conference on Computer Vision (ICCV), Honolulu, Hawaii, USA, October 2025.
[preprint (arxiv: 2503.10772)] [project website] [code]

Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation
Sucheng Ren, Qihang Yu, Ju He, Xiaohui Shen, Alan Yuille, Liang-Chieh Chen
In International Conference on Computer Vision (ICCV), Honolulu, Hawaii, USA, October 2025.
[preprint (arxiv: 2502.20388)] [project website] [code]

Democratizing Text-to-Image Masked Generative Models with Compact Text-Aware One-Dimensional Tokens
Dongwon Kim*, Ju He*, Qihang Yu*, Chenglin Yang, Xiaohui Shen, Suha Kwak, Liang-Chieh Chen
(*equal contribution)
In International Conference on Computer Vision (ICCV), Honolulu, Hawaii, USA, October 2025.
[preprint (arxiv: 2501.07730)] [project website] [code]

Randomized Autoregressive Visual Generation
Qihang Yu, Ju He, Xueqing Deng, Xiaohui Shen, Liang-Chieh Chen
In International Conference on Computer Vision (ICCV), Honolulu, Hawaii, USA, October 2025.
[preprint (arxiv: 2411.00776)] [project website] [code]

FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching
Sucheng Ren, Qihang Yu, Ju He, Xiaohui Shen, Alan Yuille, Liang-Chieh Chen
International Conference on Machine Learning (ICML), Vancouver, Canada, July 2025.
[preprint (arxiv: 2412.15205)] [code]

ViCaS: A Dataset for Combining Holistic and Pixel-level Video Understanding using Captions with Grounded Segmentation
Ali Athar, Xueqing Deng, Liang-Chieh Chen
In Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, Tennessee, USA, June 2025.
[preprint (arxiv: 2412.09754)] [project website] [code and dataset] [dataset (Hugging Face)]