Research Scientist, Shanghai AI Lab & Deputy Director of R&D, Sensetime Group.
Room 3719, Level 37, 701 Yunjin Road, Xuhui District, Shanghai, China
liyikang [at] pjlab.org.cn, liyikang [at] senseauto.com
Google scholar | Github || Weibo | Wechat | LinkedIn || Resume | 中文简历
I’m currently a research scientist & PI at Shanghai AI Laboratory and Deputy Director of R&D at Sensetime Technology Ltd.. I am leading a research team containg over 20 talented researchers & interns at Shanghai AI Lab, aiming at designing an automated data pipeline to enhance the data-driven Autonomous Driving development. Additionally, I also lead a R&D team containing over 30 talented engineers at Sensetime, developing the RoboX Autonomous Products.
I obtained my Ph.D. from The Chinese University of Hong Kong in May, 2020 supervised by Prof. Xiaogang Wang and Prof. Xiaoou Tang. I got my bachelor’s degrees of Electronic Engineering and Economics in Tsinghua University in 2016. I worked as an research intern at Microsoft Research Asia (MSRA) and Facebook Reality Labs (Now Meta Reality Labs) during my Ph.D. years.
Research interest: 3D Scene Reconstruction, 3D Scene Perception, Behavior & Scene Simulation, any Autonomous-Driving-related topic.
***Important*** Our team is searching for highly self-motivated interns / full-time employees / post-docs . If you are interested in solving the industrial problem in an academic way, do not hesitate to contact me.
|May 27, 2022||Our Calibration Toolbox for Autonomous Driving, OpenCalib (Code and Paper), is now released. NEW!|
|Mar 22, 2022||The group standard for RoboBus led by us is released. 《自动驾驶小型客车总体技术要求》|
|Mar 2, 2022||Two papers are accepted by CVPR-2022, poster * 1 and oral * 1.|
|Feb 6, 2022||Our survey paper on multi-modal sensor fusion for autonomous driving perception is now on Arxiv.|
|Jan 29, 2022||An all-in-one and ready-to-use LiDAR-inertial odometry system for Livox LiDAR is released. [Code]|
|Jan 29, 2022||Beta Testing for Data Compliance Guide (《数据合规自查表》/ 《数据合规指南》) is now open to [apply].|
CVPRPoint-to-Voxel Knowledge Distillation for LiDAR Semantic SegmentationProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022
NeurIPSPastegan: A Semi-parametric Method to Generate Image from Scene GraphAdvances in Neural Information Processing Systems (NeurIPS) 2019
ECCVFactorizable Net: an Efficient Subgraph-based Framework for Scene Graph GenerationProceedings of the European Conference on Computer Vision (ECCV) 2018
CVPRVisual Question Generation as Dual Task of Visual Question AnsweringProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2018
ICCVScene Graph Generation from Objects, Phrases and Region CaptionsProceedings of the IEEE International Conference on Computer Vision (ICCV) 2017
CVPRViP-CNN: Visual Phrase Guided Convolutional Neural NetworkProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2017
ArxivOpenCalib: A Multi-sensor Calibration Toolbox for Autonomous DrivingarXiv preprint arXiv:2205.14087 2022
ArxivJoint Camera Intrinsic and LiDAR-Camera Extrinsic CalibrationarXiv preprint arXiv:2202.13708 2022
ArxivMulti-modal Sensor Fusion for Auto Driving Perception: A SurveyarXiv preprint arXiv:2202.02703 2022
ArxivPerception Entropy: A Metric for Multiple Sensors Configuration Evaluation and DesignarXiv preprint arXiv:2104.06615 2021
ArxivCRLF: Automatic Calibration and Refinement based on Line Feature for LiDAR and Camera in Road ScenesarXiv preprint arXiv:2103.04558 2021