Unsupervised Adaptation from Repeated Traversals for Autonomous Driving
Yurong You*, Cheng Perng Phoo*, Katie Z Luo*, Travis Zhang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger
In NeurIPS, 2022
TLDR : Data captured from repeated traversals of a scene can be used to adapt 3D object detectors to new domains without supervision
pdf bibtex
```
@inproceedings{You2022Unsupervised,
title = {Unsupervised Adaptation from Repeated Traversals for Autonomous Driving},
author = {Yurong You and  Cheng Perng Phoo and  Katie Z Luo and  Travis Zhang and  Wei-Lun Chao and  Bharath Hariharan and  Mark Campbell and  Kilian Q. Weinberger},
year = {2022},
booktitle = {NeurIPS}
}
```

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

@inproceedings{You2022Exploiting,
title = {Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection},
author = {Yurong You and   Carlos Andres Diaz-Ruiz and  Yan Wang and  Wei-Lun Chao and  Bharath Hariharan and  Mark Campbell and  Kilian Weinberger},
year = {2022},
booktitle = {ICRA}
}

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

@inproceedings{You2022Learning,
title = {Learning to Detect Mobile Objects from LiDAR Scans Without Labels},
author = {Yurong You and  Katie Luo and  Cheng Perng Phoo and  Wei-Lun Chao and  Wen Sun and  Bharath Hariharan and  Mark Campbell and  Kilian Weinberger},
year = {2022},
booktitle = {CVPR}
}

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

@inproceedings{You2022Hindsight,
title = {Hindsight is 20/20: Leveraging past traversals to aid 3D perception},
author = {Yurong You and  Katie Luo and  Xiangyu Chen and  Junan Chen and  Wei-Lun Chao and  Wen Sun and  Bharath Hariharan and  Mark Campbell and  Kilian Weinberger},
year = {2022},
booktitle = {ICLR}
}

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
```
@inproceedings{Wang2020Train,
title = {Train in Germany, Test in The USA: Making 3D Object Detectors Generalize},
author = {Yan Wang and  Xiangyu Chen and  Yurong You and  Li Erran Li and  Bharath Hariharan and  Mark Campbell and  Kilian Q. Weinberger and  Wei-Lun Chao},
year = {2020},
booktitle = {CVPR}
}
```
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
```
@inproceedings{Qian2020End,
title = {End-to-end Pseudo-LiDAR for Image-Based 3D Object Detection},
author = {Rui Qian and  Divyansh Garg and  Yan Wang and  Yurong You and  Serge Belongie and  Bharath Hariharan and  Mark Campbell and  Kilian Q. Weinberger and  and Wei-Lun Chao},
year = {2020},
booktitle = {CVPR}
}
```
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
```
@inproceedings{You2020Pseudo-lidar,
title = {Pseudo-lidar++: Accurate depth for 3d object detection in autonomous driving},
author = {Yurong You and  Yan Wang and  Wei-Lun Chao and  Divyansh Garg and  Geoff Pleiss and  Bharath Hariharan and  Mark Campbell and  and Kilian Weinberger},
year = {2020},
booktitle = {ICLR}
}
```
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
```
@inproceedings{Wang2019Pseudo-lidar,
title = {Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving},
author = {Yan Wang and  Wei-Lun Chao and  Divyansh Garg and  Bharath Hariharan and  Mark Campbell and  Kilian Q. Weinberger},
year = {2019},
booktitle = {CVPR}
}
```

Publications