Jingkang Wang

According to our database, Jingkang Wang authored at least 26 papers between 2018 and 2023.

Collaborative distances:

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

2023

LightSim: Neural Lighting Simulation for Urban Scenes.

Ava Pun, Gary Sun, Jingkang Wang, Yun Chen, Ze Yang, Sivabalan Manivasagam, Wei-Chiu Ma, Raquel Urtasun

CoRR, 2023

UltraLiDAR: Learning Compact Representations for LiDAR Completion and Generation.

Yuwen Xiong, Wei-Chiu Ma, Jingkang Wang, Raquel Urtasun

CoRR, 2023

Neural Lighting Simulation for Urban Scenes.

Ava Pun, Gary Sun, Jingkang Wang, Yun Chen, Ze Yang, Sivabalan Manivasagam, Wei-Chiu Ma, Raquel Urtasun

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reconstructing Objects in-the-wild for Realistic Sensor Simulation.

Ze Yang, Sivabalan Manivasagam, Yun Chen, Jingkang Wang, Rui Hu, Raquel Urtasun

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Towards Zero Domain Gap: A Comprehensive Study of Realistic LiDAR Simulation for Autonomy Testing.

Sivabalan Manivasagam, Ioan Andrei Bârsan, Jingkang Wang, Ze Yang, Raquel Urtasun

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Real-Time Neural Rasterization for Large Scenes.

Jeffrey Yunfan Liu, Yun Chen, Ze Yang, Jingkang Wang, Sivabalan Manivasagam, Raquel Urtasun

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Learning Compact Representations for LiDAR Completion and Generation.

Yuwen Xiong, Wei-Chiu Ma, Jingkang Wang, Raquel Urtasun

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

UniSim: A Neural Closed-Loop Sensor Simulator.

Ze Yang, Yun Chen, Jingkang Wang, Sivabalan Manivasagam, Wei-Chiu Ma, Anqi Joyce Yang, Raquel Urtasun

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

2022

CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation.

Jingkang Wang, Sivabalan Manivasagam, Yun Chen, Ze Yang, Ioan Andrei Barsan, Anqi Joyce Yang, Wei-Chiu Ma, Raquel Urtasun

Proceedings of the Conference on Robot Learning, 2022

2021

Just Label What You Need: Fine-Grained Active Selection for Perception and Prediction through Partially Labeled Scenes.

Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun

CoRR, 2021

Cost-Efficient Online Hyperparameter Optimization.

Jingkang Wang, Mengye Ren, Ilija Bogunovic, Yuwen Xiong, Raquel Urtasun

CoRR, 2021

Adversarial Attack Generation Empowered by Min-Max Optimization.

Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Policy Learning Using Weak Supervision.

Jingkang Wang, Hongyi Guo, Zhaowei Zhu, Yang Liu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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

Just Label What You Need: Fine-Grained Active Selection for P&P through Partially Labeled Scenes.

Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun

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

2020

BabyAI++: Towards Grounded-Language Learning beyond Memorization.

Tianshi Cao, Jingkang Wang, Yining Zhang, Sivabalan Manivasagam

CoRR, 2020

On the Impact of Perceptual Compression on Deep Learning.

Gerald Friedland, Ruoxi Jia, Jingkang Wang, Bo Li, T. Nathan Mundhenk

Proceedings of the 3rd IEEE Conference on Multimedia Information Processing and Retrieval, 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

Reinforcement Learning with Perturbed Rewards.

Jingkang Wang, Yang Liu, Bo Li

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Beyond Adversarial Training: Min-Max Optimization in Adversarial Attack and Defense.

Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li

CoRR, 2019

Multiple Character Embeddings for Chinese Word Segmentation.

Jianing Zhou, Jingkang Wang, Gongshen Liu

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

One Bit Matters: Understanding Adversarial Examples as the Abuse of Redundancy.

Jingkang Wang, Ruoxi Jia, Gerald Friedland, Bo Li, Costas J. Spanos

CoRR, 2018

The Helmholtz Method: Using Perceptual Compression to Reduce Machine Learning Complexity.

Gerald Friedland, Jingkang Wang, Ruoxi Jia, Bo Li

CoRR, 2018

LiDAR-Video Driving Dataset: Learning Driving Policies Effectively.

Yiping Chen, Jingkang Wang, Jonathan Li, Cewu Lu, Zhipeng Luo, Han Xue, Cheng Wang

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018