James Tu

According to our database, James Tu authored at least 16 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

MIXSIM: A Hierarchical Framework for Mixed Reality Traffic Simulation.

Simon Suo, Kelvin Wong, Justin Xu, James Tu, Alexander Cui, Sergio Casas, Raquel Urtasun

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Learning Realistic Traffic Agents in Closed-loop.

Chris Zhang, James Tu, Lunjun Zhang, Kelvin Wong, Simon Suo, Raquel Urtasun

Proceedings of the Conference on Robot Learning, 2023

Towards Scalable Coverage-Based Testing of Autonomous Vehicles.

James Tu, Simon Suo, Chris Zhang, Kelvin Wong, Raquel Urtasun

Proceedings of the Conference on Robot Learning, 2023

Adv3D: Generating Safety-Critical 3D Objects through Closed-Loop Simulation.

Jay Sarva, Jingkang Wang, James Tu, Yuwen Xiong, Sivabalan Manivasagam, Raquel Urtasun

Proceedings of the Conference on Robot Learning, 2023

2021

3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI.

Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu, James Tu, Nipaporn Tewattanarat, Sayali Joshi, Andrea Doria, Anna Goldenberg

CoRR, 2021

Diverse Complexity Measures for Dataset Curation in Self-Driving.

Abbas Sadat, Sean Segal, Sergio Casas, James Tu, Bin Yang, Raquel Urtasun, Ersin Yumer

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Adversarial Attacks On Multi-Agent Communication.

James Tu, Tsun-Hsuan Wang, Jingkang Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles.

Jingkang Wang, Ava Pun, James Tu, Sivabalan Manivasagam, Abbas Sadat, Sergio Casas, Mengye Ren, Raquel Urtasun

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Exploring Adversarial Robustness of Multi-sensor Perception Systems in Self Driving.

James Tu, Huichen Li, Xinchen Yan, Mengye Ren, Yun Chen, Ming Liang, Eilyan Bitar, Ersin Yumer, Raquel Urtasun

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

StrObe: Streaming Object Detection from LiDAR Packets.

Davi Frossard, Simon Suo, Sergio Casas, James Tu, Rui Hu, Raquel Urtasun

CoRR, 2020

V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction.

Tsun-Hsuan Wang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wenyuan Zeng, James Tu, Raquel Urtasun

CoRR, 2020

Physically Realizable Adversarial Examples for LiDAR Object Detection.

James Tu, Mengye Ren, Siva Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun

CoRR, 2020

Physically Realizable Adversarial Examples for LiDAR Object Detection.

James Tu, Mengye Ren, Sivabalan Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Learning to Communicate and Correct Pose Errors.

Nicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, Raquel Urtasun

Proceedings of the 4th Conference on Robot Learning, 2020

StrObe: Streaming Object Detection from LiDAR Packets.

Davi Frossard, Shun Da Suo, Sergio Casas, James Tu, Raquel Urtasun

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Spear: Optimized Dependency-Aware Task Scheduling with Deep Reinforcement Learning.

Zhiming Hu, James Tu, Baochun Li

Proceedings of the 39th IEEE International Conference on Distributed Computing Systems, 2019