Tao Ma  

I am currently a 2nd-year Ph.D. candidate at Multimedia Laboratory (MMLab) of The Chinese University of Hong Kong, supervised by Prof. Hongsheng Li and Prof. Xiaogang Wang. My research focuses on scene perception and understanding in autonomous driving, which mainly includes onboard and offboard 3D object detection with point cloud and image data.

Better research, better life. I love cycling sports, please feel free to contact me if you have any questions or similar interests.

SHB 310, CUHK, Hong Kong SAR, China

Email  /  Google Scholar  /  Github  /  LinkedIn

News

Education

Working Experience

Publications

* indicates equal contribution to the work.

• VeloVox: A Low-cost and Accurate 4D Object Detector with Single-frame Point Cloud of Livox LiDAR
  T. Ma*, Z. Zheng*, H. Zhou, X. Cai, X. Yang, Y. Li, B. Shi, H. Li
  IEEE International Conference on Robotics and Automation (ICRA), 2024
  [arXiv]
• DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models
  L. Wen*, D. Fu*, X. Li*, X. Cai, T. Ma, P. Cai, M. Dou, B. Shi, L. He, Y. Qiao
  International Conference on Learning Representations (ICLR), 2024
  [arXiv / Project Page]
• DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds
  T. Ma, X. Yang, H. Zhou, X. Li, B. Shi, J. Liu, Y. Yang, Z. Liu, L. He, Y. Qiao, Y. Li, H. Li
  International Conference on Computer Vision (ICCV), 2023
  [arXiv / Code / Project Page]
• RangePerception: Taming LiDAR Range View for Efficient and Accurate 3D Object Detection
  Y. Bai, B. Fei, Y. Liu, T. Ma, Y. Hou, B. Shi, Y. Li
  Conference on Neural Information Processing Systems (NeurIPS), 2023
  [arXiv]
• LogoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion
  X. Li, T. Ma, Y. Hou, B. Shi, Y. Yang, Y. Liu, X. Wu, Q. Chen, Y. Li, Y. Qiao, L. He
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
  [arXiv / Code]
• Speech Fusion to Face: Bridging the Gap Between Human's Vocal Characteristics and Facial Imaging
  Y. Bai, T. Ma, L. Wang, Z. Zhang
  ACM International Conference on Multimedia (ACM MM), 2022
  [arXiv]
• PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph
  Y. Li*, T. Ma*, Y. Bai, N. Duan, S. Wei, X. Wang
  Conference on Neural Information Processing Systems (NeurIPS), 2019
  [arXiv / code]

Preprints

* indicates equal contribution to the work.

• Towards Knowledge-driven Autonomous Driving
  X. Li, Y. Bai, P. Cai, L. Wen, D. Fu, B. Zhang, X. Yang, X. Cai, T. Ma, J. Guo, X. Gao, M. Dou, Y. Li, B. Shi, Y. Liu, L. He, Y. Qiao
  arXiv preprint, 2023
  [arXiv]
• On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving
  L. Wen, X. Yang, D. Fu, X. Wang, P. Cai, X. Li, T. Ma, Y. Li, L. Xu, D. Shang, Z. Zhu, S. Sun, Y. Bai, X. Cai, M. Dou, S. Hu, B. Shi, Y. Qiao
  arXiv preprint, 2023
  [arXiv]
• Opencalib: A multi-sensor calibration toolbox for autonomous driving
  G. Yan, Z. Liu, C. Wang, C. Shi, P. Wei, X. Cai, T. Ma, Z. Liu, Z. Zhong, Y. Liu, M. Zhao, Z. Ma, Y. Li
  arXiv preprint, 2022
  [arXiv]
• CRLF: Automatic Calibration and Refinement based on Line Feature for LiDAR and Camera in Road Scenes
  T. Ma*, Z. Liu*, G. Yan, Y. Li
  arXiv preprint, 2020
  [arXiv]
• Perception Entropy: A Metric for Multiple Sensors Configuration Evaluation and Design
  T. Ma*, Z. Liu*, Y. Li
  arXiv preprint, 2020
  [arXiv]
• MOC-GAN: Mixing Objects and Captions to Generate Realistic Images
  T. Ma, Y. Li
  arXiv preprint, 2020
  [arXiv]

Academic Activities

Teaching