Peng YUN

I got my Ph.D. degree in 2023.01 from the Hong Kong University of Science and Technology, supervised by Prof. Ming LIU in RAM-Lab. I received my bachelor degree in 2017 from Huazhong University of Science and Technology. I joined HKUST RoboCup as a team member in 2017. Since then, I started my robotic work.

Email / Google Scholar / CV

Research

My research interests include 3D object detection, incremental learning, Bayesian neural networks, uncertainty estimation, and autonomous driving applications. Representative papers are highlighted.

	Accurate and robust visual localization system in large-scale appearance-changing environments IEEE/ASME Transactions on Mechatronics, 2022 Yang Yu, Peng Yun, Bohuan Xue, Jianhao Jiao, Rui Fan, Ming Liu pdf / bibtex
	Laplace Approximation Based Epistemic Uncertainty Estimation in 3D Object Detection Conference on Robotic Learning, 2022 Peng Yun, Ming Liu pdf / bibtex / video
	Open-world semantic segmentation for lidar point clouds ECCV 2022 Jun Cen, Peng Yun, Shiwei Zhang, Junhao Cai, Di Luan, Mingqian Tang, Ming Liu, Michael Yu Wang pdf / bibtex / code / video
	Open-set 3D object detection International Conference on 3D Vision (3DV), 2021 Jun Cen, Peng Yun, Junhao Cai, Michael Yu Wang, Ming Liu pdf / bibtex
	Conflicts between likelihood and knowledge distillation in task incremental learning for 3d object detection International Conference on 3D Vision (3DV), 2021 Peng Yun, Jun Cen, Ming Liu pdf / bibtex / video
	Deep metric learning for open world semantic segmentation IEEE/CVF International Conference on Computer Vision, 2021 Jun Cen, Peng Yun, Junhao Cai, Michael Yu Wang, Ming Liu pdf / bibtex
	FuseSeg: Semantic Segmentation of Urban Scenes Based on RGB and Thermal Data Fusion IEEE Transactions on Automation Science and Engineering (T-ASE), 2020 Yuxiang Sun, Weixun Zuo, Peng Yun, Hengli Wang, Ming Liu pdf / bibtex / video
	In Defense of Knowledge Distillation for Task Incremental Learning and Its Application in 3D Object Detection. RAL, 2021 Peng Yun*, Yuxuan Liu, Ming Liu pdf / bibtex / project page / code
	MLOD: Awareness of Extrinsic Perturbation in Multi-LiDAR 3D Object Detection for Autonomous Driving. IROS, 2020 Jianhao Jiao, Peng Yun, Yuying Chen, Congcong Liu, Haoyang Ye, Ming Liu (* indicates equal contribution) pdf / bibtex / video / code / dataset
	Visual-based Autonomous Driving Deployment from a Stochastic and Uncertainty-aware Perspective. IROS, 2019 Lei Tai, Peng Yun, Yuying Chen, Congcong Liu, Haoyang Ye, Ming Liu pdf / bibtex / video / code
	Focal Loss in 3D Object Detection. IEEE Robotics and Automation Letters (RA-L), 2019 ICRA, 2019 Peng Yun, Lei Tai, Yuan Wang, Chengju Liu, Ming Liu pdf / bibtex / page / code
	VR-Goggles for Robots: Real-to-sim Domain Adaptation for Visual Control. IEEE Robotics and Automation Letters (RA-L), 2019 Jingwei Zhang, Lei Tai, Peng Yun, Yufeng Xiong, Ming Liu, Joschka Boedecker, Wolfram Burgard (*indicates equal contribution) pdf / bibtex / supplement / page / video
	Pointseg: Real-time semantic segmentation based on 3d lidar point cloud. arXiv preprint arXiv:1807.06288 Yuan Wang, Tianyue Shi, Peng Yun, Lei Tai, Ming Liu pdf / bibtex / code
	Towards a Cloud Robotics Platform for Distributed Visual SLAM. International Conference on Computer Vision Systems (ICVS), 2017 Peng Yun, Jianhao Jiao, Ming Liu pdf / bibtex
	A Cloud-Based Visual SLAM framework for Low-Cost Agents, International Conference on Computer Vision Systems. International Conference on Computer Vision Systems (ICVS), 2017 Jianhao Jiao, Peng Yun, Ming Liu pdf / bibtex

Demo

There are some demos for 3D object detection of some work in progress. Just for visulization. :)

Made from Dr. Jon Barron's website.