@inproceedings{xiangyu2024diffuBox,author={Chen, Xiangyu and Liu, Zhenzhen and Luo, Katie Z. and Datta, Siddhartha and Polavaram, Adhitya and Wang, Yan and You, Yurong and Li, Boyi and Pavone, Marco and Chao, Wei-Lun and Campbell, Mark E. and Hariharan, Bharath and Weinberger, Kilian Q.},booktitle={the Conference on Neural Information Processing Systems (NeurIPS)},title={DiffuBox: Refining 3D Object Detection with Point Diffusion},year={2024},month=dec,}
ICLR
Pre-training LiDAR-based 3D Object Detectors through Colorization
@inproceedings{pan2024pretraining,title={Pre-training Li{DAR}-based 3D Object Detectors through Colorization},author={Pan, Tai-Yu and Ma, Chenyang and Chen, Tianle and Phoo, Cheng Perng and Luo, Katie Z and You, Yurong and Campbell, Mark and Weinberger, Kilian Q and Hariharan, Bharath and Chao, Wei-Lun},booktitle={the International Conference on Learning Representations (ICLR)},year={2024},month=jun,url={https://openreview.net/forum?id=fB1iiH9xo7}}
ICRA
Better Monocular 3D Detectors with LiDAR from the Past
@inproceedings{you2024asyncdepth,author={You, Yurong and Phoo, Cheng Perng and Diaz-Ruiz, Carlos Andres and Luo, Katie Z and Chao, Wei-Lun and Campbell, Mark and Hariharan, Bharath and Weinberger, Kilian Q},booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA)},title={Better Monocular 3D Detectors with LiDAR from the Past},year={2024},month=apr,volume={},number={},pages={6634-6641},keywords={Three-dimensional displays;Laser radar;Costs;Detectors;Object detection;Performance gain;Feature extraction},doi={10.1109/ICRA57147.2024.10610444},}
2023
NeurIPS
Teaching Cars to See in a Day: Unsupervised Object Discovery with Reward Fine-tuning
@inproceedings{you2022unsupervisee,title={Teaching Cars to See in a Day: Unsupervised Object Discovery with Reward Fine-tuning},author={Luo, Katie Z and Liu, Zhenzhen and Chen, Xiangyu and You, Yurong and Benaim, Sagie and Phoo, Cheng Perng and Campbell, Mark and Sun, Wen and Hariharan, Bharath and Weinberger, Kilian Q.},booktitle={the Conference on Neural Information Processing Systems (NeurIPS)},year={2023},month=dec}
2022
NeurIPS
Unsupervised Adaptation from Repeated Traversals for Autonomous Driving
@inproceedings{you2022unsupervised,title={Unsupervised Adaptation from Repeated Traversals for Autonomous Driving},author={You, Yurong and Phoo, Cheng Perng and Luo, Katie Z and Zhang, Travis and Chao, Wei-Lun and Hariharan, Bharath and Campbell, Mark and Weinberger, Kilian Q.},booktitle={the Conference on Neural Information Processing Systems (NeurIPS)},year={2022},month=dec}
CVPR
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions
@inproceedings{carlos2022ithaca365,title={Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions},author={Diaz-Ruiz, Carlos Andres and Xia, Youya and You, Yurong and Nino, Jose and Chen, Junan and Monica, Josephine and Chen, Xiangyu and Luo, Katie Z and Wang, Yan and Emond, Marc and Chao, Wei-Lun and Hariharan, Bharath and Weinberger, Kilian Q. and Campbell, Mark},booktitle={the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},year={2022},month=jun}
CVPR
Learning to Detect Mobile Objects from LiDAR Scans Without Labels
@inproceedings{you2022learning,title={Learning to Detect Mobile Objects from LiDAR Scans Without Labels},author={You, Yurong and Luo, Katie Z and Phoo, Cheng Perng and Chao, Wei-Lun and Sun, Wen and Hariharan, Bharath and Campbell, Mark and Weinberger, Kilian Q.},booktitle={the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},year={2022},month=jun}
ICRA
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection
@inproceedings{you2022exploiting,title={Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection},author={You, Yurong and Diaz-Ruiz, Carlos Andres and Wang, Yan and Chao, Wei-Lun and Hariharan, Bharath and Campbell, Mark and Weinberger, Kilian Q.},booktitle={the IEEE International Conference on Robotics and Automation (ICRA)},year={2022},month=may}
ICRA
Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking
@inproceedings{longlong2022exploiting,title={Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking},author={Jing, Longlong and Yu, Ruichi and Kretzschmar, Henrik and Li, Kang and Qi, Ruizhongtai and Zhao, Hang and Ayvaci, Alper and Chen, Xu and Cower, Dillon and Li, Yingwei and You, Yurong and Deng, Han and Li, Congcong and Anguelov, Dragomir},booktitle={the IEEE International Conference on Robotics and Automation (ICRA)},year={2022},month=may}
ICLR
R4D: Utilizing Reference Objects for Long-Range Distance Estimation
@inproceedings{li2022rd,title={R4D: Utilizing Reference Objects for Long-Range Distance Estimation},author={Li, Yingwei and Chen, Tiffany and Kabkab, Maya and Yu, Ruichi and Jing, Longlong and You, Yurong and Zhao, Hang},booktitle={International Conference on Learning Representations},year={2022},month=apr,url={https://openreview.net/forum?id=MQ2sAGunyBP}}
ICLR
Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception
@inproceedings{you2022hindsight,title={Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception},author={You, Yurong and Luo, Katie Z and Chen, Xiangyu and Chen, Junan and Chao, Wei-Lun and Sun, Wen and Hariharan, Bharath and Campbell, Mark and Weinberger, Kilian Q.},booktitle={the International Conference on Learning Representations (ICLR)},year={2022},month=apr,url={https://openreview.net/forum?id=qsZoGvFiJn1},}
2020
CVPR
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection
@inproceedings{Qian_2020_CVPR,author={Qian, Rui and Garg, Divyansh and Wang, Yan and You, Yurong and Belongie, Serge and Hariharan, Bharath and Campbell, Mark and Weinberger, Kilian Q. and Chao, Wei-Lun},title={End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection},booktitle={the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month=jun,year={2020}}
CVPR
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize
@inproceedings{wang2020train,title={Train in Germany, Test in The USA: Making 3D Object Detectors Generalize},author={Wang, Yan and Chen, Xiangyu and You, Yurong and Li, Li Erran and Hariharan, Bharath and Campbell, Mark and Weinberger, Kilian Q. and Chao, Wei-Lun},booktitle={the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},pages={11713--11723},year={2020},month=jun}
ICLR
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
@inproceedings{You2020PseudoLiDARpp:,title={Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving},author={You, Yurong and Wang, Yan and Chao, Wei-Lun and Garg, Divyansh and Pleiss, Geoff and Hariharan, Bharath and Campbell, Mark and Weinberger, Kilian Q.},booktitle={the International Conference on Learning Representations (ICLR)},year={2020},month=apr,url={https://openreview.net/forum?id=BJedHRVtPB},}
@inproceedings{guo2019simple,title={Simple Black-box Adversarial Attacks},author={Guo, Chuan and Gardner, Jacob and You, Yurong and Wilson, Andrew Gordon and Weinberger, Kilian Q.},booktitle={the International Conference on Machine Learning (ICML)},pages={2484--2493},year={2019}}
2018
CVPR
Resource Aware Person Re-Identification Across Multiple Resolutions
@inproceedings{Wang2018CVPR,author={Wang, Yan and Wang, Lequn and You, Yurong and Zou, Xu and Chen, Vincent and Li, Serena and Huang, Gao and Hariharan, Bharath and Weinberger, Kilian Q.},title={Resource Aware Person Re-Identification Across Multiple Resolutions},booktitle={the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month=jun,year={2018}}
2017
BMVC
Virtual to Real Reinforcement Learning for Autonomous Driving
@inproceedings{BMVC2017,title={Virtual to Real Reinforcement Learning for Autonomous Driving},author={Pan, Xinlei and You, Yurong and Wang, Ziyan and Lu, Cewu},year={2017},month=sep,pages={11.1-11.13},articleno={11},numpages={13},booktitle={the British Machine Vision Conference (BMVC)},publisher={BMVA Press},editor={Tae-Kyun Kim, Stefanos Zafeiriou, Gabriel Brostow and Mikolajczyk, Krystian},doi={10.5244/C.31.11},isbn={1-901725-60-X}}