Publications

  • Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection
    Yurong You*, Carlos Andres Diaz-Ruiz*, Yan Wang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Weinberger
    In ICRA, 2022
    TLDR : Extrapolating tracks of detected objects yields good ground truth for adapting 3D detectors
    pdf    bibtex
  • Learning to Detect Mobile Objects from LiDAR Scans Without Labels
    Yurong You*, Katie Luo*, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark Campbell, Kilian Weinberger
    In CVPR, 2022
    TLDR : Can we train a 3D object detector without labels by simply driving around?
    pdf    bibtex
  • Hindsight is 20/20: Leveraging past traversals to aid 3D perception
    Yurong You, Katie Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark Campbell, Kilian Weinberger
    In ICLR, 2022
    TLDR : Can past traversals through a dynamic scene help 3D perception of the current scene?
    pdf    bibtex
  • Train in Germany, Test in The USA: Making 3D Object Detectors Generalize
    Yan Wang, Xiangyu Chen, Yurong You, Li Erran Li, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao
    In CVPR, 2020
    TLDR : Domain differences lead to catastrophic failures in 3D object detection. We present a simple and effective remedy.
    pdf    supp    bibtex
  • End-to-end Pseudo-LiDAR for Image-Based 3D Object Detection
    Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge Belongie, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, and Wei-Lun Chao
    In CVPR, 2020
    TLDR : We learn in an end-to-end manner how best to represent estimated depth for 3D object detection from stereo
    pdf    supp    bibtex
  • Pseudo-lidar++: Accurate depth for 3d object detection in autonomous driving
    Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, and Kilian Weinberger
    In ICLR, 2020
    TLDR : We can effectively replace expensive LiDAR with a combination of a cheaper, sparser LiDAR scanners and a higher quality stereo depth estimator
    pdf    code    bibtex
  • Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
    Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger
    In CVPR, 2019
    TLDR : We close the gap between vision-based and LiDAR-based 3D object detection by simply changing how estimated depth is represented in the model
    pdf    supp    project page    bibtex