Yingwei Li

A research scientist @ Waymo

Email: ywli@waymo.com

About Me

Hi! I am a research scientist at Waymo. I received my Ph.D. degree from Computer Science department at Johns Hopkins University, advised by Bloomberg Distinguished Professor Dr. Alan Yuille.

I obtained B.S. in Computer Science at Fudan University in 2018. I also spent time at Google Research, Waymo, ByteDance, NTU, and TuSimple.

My research interests mainly lie in computer vision, especially in autonomous driving, robust representation learning, multi-modality fusion, automated machine learning, and medical machine intelligence.

News

NEW [02/27/2022] One paper is accepted by CVPR 2023.

[10/10/2022] One paper is accepted by WACV 2023.

[09/17/2022] One paper is accepted by ACM CCS 2022.

[07/03/2022] One paper is accepted by ECCV 2022.

[06/06/2022] Begin my full-time work journey!

(view more)

Selected Publications

MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences

Yingwei Li*, Charles R. Qi*, Yin Zhou, Chenxi Liu, Dragomir Anguelov

CVPR, 2023
[Paper] [Supplementary] [Bibtex]

Context Enhanced Stereo Transformer

Weiyu Guo, Zhaoshuo Li, Yongkui Yang, Zheng Wang, Russ Taylor, Mathias Unberath, Alan Yuille, Yingwei Li

ECCV, 2022
[Paper] [Code] [Bibtex]

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection

Yingwei Li*, Adams Yu*, Tianjian Meng, Ben Caine, Jiquan Ngiam, Daiyi Peng, Junyang Shen, Bo Wu, Yifeng Lu, Denny Zhou, Quoc Le, Alan Yuille, Mingxing Tan

CVPR, 2022
[Paper] [Code] [Website] [Bibtex]

Learning from Temporal Gradient for Semi-supervised Action Recognition

Junfei Xiao, Longlong Jing, Lin Zhang, Ju He, Qi She, Zongwei Zhou, Alan Yuille, Yingwei Li

CVPR, 2022
[Paper] [Code] [Bibtex]

R4D: Utilizing Reference Objects for Long-Range Distance Estimation

Yingwei Li, Tiffany Chen*, Maya Kabkab*, Ruichi Yu, Longlong Jing, Yurong You, Hang Zhao

ICLR, 2022
[Paper] [Supplementary] [Bibtex]

Shape-Texture Debiased Neural Network Training

Yingwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan Yuille, Cihang Xie

ICLR, 2021
[Paper] [Code] [Website] [Video] [Bibtex]

Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses

Yingwei Li, Song Bai, Cihang Xie, Zhenyu Liao, Xiaohui Shen, Alan Yuille

ECCV, 2020
[Paper] [Code] [Bibtex]

Neural Architecture Search for Lightweight Non-Local Networks

Yingwei Li, Xiaojie Jin, Jieru Mei, Xiaochen Lian, Linjie Yang, Cihang Xie, Qihang Yu, Yuyin Zhou, Song Bai, Alan Yuille

CVPR, 2020
[Paper] [Code] [Bibtex]

Learning Transferable Adversarial Examples via Ghost Networks

Yingwei Li, Song Bai, Yuyin Zhou, Cihang Xie, Zhishuai Zhang, Alan Yuille

AAAI, 2020
CVPR Workshop (Oral), 2019
[Paper] [Code] [Bibtex]

Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-Fine Framework and Its Adversarial Examples

Yingwei Li*, Zhuotun Zhu* Yuyin Zhou, Yingda Xia, Wei Shen, Elliot K Fishman, Alan Yuille

Book Chapter: Deep Learning and CNN for Medical Image Computing , 2019
[Paper] [Bibtex]

→ Full list

Affiliations

Academic Service

Co-organizer

Adversarial Robustness in the Real World @ ECCV 2022
The Art of Robustness: Devil and Angel in Adversarial Machine Learning @ CVPR 2022
Practical Deep Learning in the Wild @ AAAI 2022
Adversarial Robustness in the Real World @ ICCV 2021
Adversarial Learning for Multimedia @ ACMMM 2021
Adversarial Robustness in the Real World @ ECCV 2020

Reviewer

Journal: IEEE TIP, IEEE TDSC, Neurocomputing, Pattern Recognition.
Conference: AmlCV@CVPR2020, SRML@ICML2021, SecMl@ICLR2021, RseMl@AAAI2021 AAAI 2021, IJCAI 2021, CVPR 2021, ICCV 2021, NeurIPS 2021, AAAI 2022, ICLR 2022, CVPR 2022, ICML 2022.