Yuliang Zou

Senior Research Scientist
Applied Research Team
Waymo LLC
ylzou [at] waymo [dot] com

About

Bio

I am a Senior Research Scientist at Waymo (formerly the Google self-driving car project).

At Waymo, I develop new technologies for autonomous vehicles across various domains including perception, planning, simulation, and mapping.

Over the summers, I have (co-)hosted the following talented interns.

- Meng-Li Shih (University of Washington)

- Yang Fu (UC San Diego, Next: Nvidia)

- Zehao Zhu (UT Austin, Next: Waymo)

- Tianyuan Huang (Stanford, Next: Waymo)

Me in 2016

Education

Aug. 2017 - May. 2022

Aug. 2015 - Apr. 2017

Sep. 2011 - Jun. 2015

Industry

May. 2021 - Aug. 2021

Jul. 2022 - Now

May. 2020 - Aug. 2020

May. 2019 - Aug. 2019

May. 2018 - Aug. 2018

News

[2026/06]     

One paper has been accepted IROS 2026! Stay tuned!

[2026/05]     

We have released a tech report summarizing our findings in 3D perception model scaling!

[2026/04]     

Our paper, "Scene Reconstruction as Mapping Priors for 3D Detection" has been selected as Highlight in CVPR 2026!

[2026/02]     

Two papers have been accepted CVPR 2026!

[2025/11]     

We have released a tech report of our Waymo Vision-based End-to-End Driving dataset and challenge!

[2025/06]     

One paper has been accepted IROS 2025!

[2025/05]     

Our co-CEO, Dmitri Dolgov, featured our SceneCrafter at Google I/O 2025!

[2025/03]     

Our VP and Head of Research, Drago Anguelov, featured our SceneCrafter at Nvidia GTC 2025!

[2025/02]     

My first paper at Waymo has been accepted to CVPR 2025!

Publications

STELLAR: Scaling 3D Perception Large Models for Autonomous Driving

3D Perception Model Scaling

Yingwei Li, Xin Huang, Yang Liu, Yang Fu, Alex Zihao Zhu, Chen Song, Junwen Yao, Anant Subramanian, Hao Xiang, Weijing Shi, Yuliang Zou, Tom Hoddes, Zhaoqi Leng, Govind Thattai, Dragomir Anguelov, Mingxing Tan

[arXiv]

Scene Reconstruction as Mapping Priors for 3D Detection

3D Detection Sensor Fusion

Yang Fu, Yuliang Zou, Hao Xiang, Xin Huang, Yijing Bai, Chen Song, Weijing Shi, Govind Thattai, Dragomir Anguelov, Mingxing Tan, Yingwei Li

Conference on Computer Vision and Pattern Recognition (CVPR), 2026. Highlight

[arXiv] [Paper]

WOD-E2E: Waymo Open Dataset for End-to-End Driving in Challenging Long-tail Scenarios

End-to-end driving

Runsheng Xu, Hubert Lin, Wonseok Jeon, Hao Feng, Yuliang Zou, Liting Sun, John Gorman, Kate Tolstaya, Sarah Tang, Brandyn White, Ben Sapp, Mingxing Tan, Jyh-Jing Hwang, Dragomir Anguelov

Conference on Computer Vision and Pattern Recognition (CVPR), 2026.

[arXiv]

Drive&Gen: Co-Evaluating End-to-End Driving and Video Generation Models

Diffusion Models Sensor Simulation End-to-end driving

Jiahao Wang, Zhenpei Yang, Yijing Bai, Yingwei Li, Yuliang Zou, Bo Sun, Abhijit Kundu, Jose Lezama, Luna Yue Huang, Zehao Zhu, Jyh-Jing Hwang, Dragomir Anguelov, Mingxing Tan, Chiyu “Max” Jiang

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025. Oral

[arXiv]

SceneCrafter: Controllable Multi-View Driving Scene Editing

Diffusion Models Image Editing Sensor Simulation

Zehao Zhu, Yuliang Zou, Chiyu “Max” Jiang, Bo Sun, Vincent Casser, Xiukun Huang, Jiahao Wang, Zhenpei Yang, Ruiqi Gao, Leonidas Guibas, Mingxing Tan, Dragomir Anguelov

Conference on Computer Vision and Pattern Recognition (CVPR), 2025.

[arXiv] [Paper] [Nvidia GTC Talk (staring at 37:21)] [Google I/O Talk (staring at 19:07)]

Multi-Teacher Invariance Distillation for Domain-Generalized Action Recognition

Action Recognition Domain Generalization

Jongmin Shin, Abhishek Maiti, Yuliang Zou, Jinwoo Choi

International Conference on Pattern Recognition (ICPR), 2024. Oral

[Paper]

Learning Representational Invariances for Data-Efficient Action Recognition

Action Recognition Data Augmentation Semi-Supervised Learning

Yuliang Zou, Jinwoo Choi*, Qitong Wang, Jia-Bin Huang
(* corresponding author)

Computer Vision and Image Understanding (CVIU), 2023.

[arXiv] [Code] [Project Page]


Learning Instance-Specific Adaptation for Cross-Domain Segmentation

Panoptic Segmentation Semantic Segmentation Test-Time Adaptation Transfer Learning

Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang

European Conference on Computer Vision (ECCV), 2022.

[arXiv] [Code] [Project Page]


PseudoSeg: Designing Pseudo Labels for Semantic Segmentation

Semantic Segmentation Semi-Supervised Learning

Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister

International Conference on Learning Representations (ICLR), 2021.

[arXiv] [Code] [Poster] [Project Page]

Learning Monocular Visual Odometry via Self-Supervised Long-Term Modeling

Sequential Learning Unsupervised Learning Visual Odometry

Yuliang Zou, Pan Ji, Quoc-Huy Tran, Jia-Bin Huang, Manmohan Chandraker

European Conference on Computer Vision (ECCV), 2020.

[arXiv] [Project Page]

DRG: Dual Relation Graph for Human-Object Interaction Detection

Graph Network Scene Understanding

Chen Gao, Jiarui Xu, Yuliang Zou, Jia-Bin Huang

European Conference on Computer Vision (ECCV), 2020.

[arXiv] [Code] [Project Page]

Reducing Footskate in Human Motion Reconstruction with Ground Contact Constraints

Human Sensing

Yuliang Zou, Jimei Yang, Duygu Ceylan, Jianming Zhang, Federico Perazzi, Jia-Bin Huang

Winter Conference on Applications of Computer Vision (WACV), 2020. Oral

[Code] [Data] [Paper] [Poster] [Project Page] [Video]

DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency

Depth Estimation Optical Flow Unsupervised Learning

Yuliang Zou, Zelun Luo, Jia-Bin Huang

European Conference on Computer Vision (ECCV), 2018.

[arXiv] [Code] [Poster] [Project Page]

iCAN: Instance-Centric Attention Network for Human-Object Interaction Detection

Object Detection Scene Understanding

Chen Gao, Yuliang Zou, Jia-Bin Huang

British Machine Vision Conference (BMVC), 2018

[arXiv] [Code] [Project Page]

Label-Efficient Learning of Transferable Representations across Domains and Tasks

Domain Adaptation Semi-Supervised Learning Transfer Learning

Zelun Luo, Yuliang Zou, Judy Hoffman, Li Fei-Fei

Neural Information Processing Systems (NeurIPS), 2017

[arXiv] [Poster] [Project Page]

Learning to Generate Long-term Future via Hierarchical Prediction

Generative Modeling

Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee

International Conference on Machine Learning (ICML), 2017

[arXiv] [Code] [Poster] [Project Page] [Slides] [SOHU News (Chinese)]

"欲买桂花同载酒,终不似,少年游。"