3D perception

All by Year3D PerceptionRobustnessMulti ModalityAutoML

Representative papers are shown with red border

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]

Class-Level Confidence Based 3D Semi-Supervised Learning

Zhimin Chen, Longlong Jing, Liang Yang, Yingwei Li, and Bing Li

WACV, 2023
[Paper] [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]

Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking

Longlong Jing, Ruichi Yu, Jiyang Gao, Henrik Kretzschmar, Kang Li, Charles R. Qi, Hang Zhao, Alper Ayvaci, Xu Chen, Dillon Cower, Yingwei Li, Yurong You, Han Deng, Congcong Li, Dragomir Anguelov

ICRA, 2022

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]