Shaoshuai SHI

Ph.D. Student
The Chinese University of Hong Kong

Email: shaoshuaics [at] gmail [dot] com

[Google Scholar]   [GitHub]   [CV]

About Me


I am currently a Ph.D. student in Multimedia Lab (MMLab), The Chinese University of Hong Kong (CUHK), supervised by Prof. Xiaogang Wang and Prof. Hongsheng Li. Before that, I received my bachelor’s degree from the Computer Science Honor Class of Harbin Institute Technology (HIT) in July 2017. I am about to graduate in the summer of 2021.

My research interests focus on computer vision and deep learning, especially the 3D scene understanding and object detection on the autonomous driving scenarios.

News


Codebase


Publications


ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection
Jihan Yang*, Shaoshuai Shi*, Zhe Wang, Hongsheng Li, Xiaojuan Qi (*co-first authors)
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[PDF]   [Bibtex]   [Code]  
Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds
Bowen Cheng, Lu Sheng, Shaoshuai Shi, Ming Yang, Dong Xu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[Coming Soon]  
PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detection
Shaoshuai Shi, Li Jiang, Jiajun Deng, Zhe Wang, Chaoxu Guo, Jianping Shi, Xiaogang Wang, Hongsheng Li
Technical report, arXiv:2102.00463
[PDF]   [Bibtex]  
Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
Jiajun Deng, Shaoshuai Shi, Peiwei Li, Wengang Zhou, Yanyong Zhang, Houqiang Li
AAAI Conference on Artificial Intelligence (AAAI), 2021
[PDF]   [Bibtex]   [Code]  
The Top-Performing LiDAR-only Solutions for 3D Detection / 3D Tracking / Domain Adaptation of Waymo Open Dataset Challenges
Shaoshuai Shi, Chaoxu Guo, Jihan Yang, Hongsheng Li
Technical report of top-performing LiDAR-only solutions to Waymo Open Dataset Challenges at Workshop of CVPR 2020.
[PDF]   [Bibtex]   [Code]   GitHub stars
Ranked 1st place among all LiDAR-only methods on 3D Detection, 3D Tracking, Domain Adaptation three tracks of the Waymo Open Dataset challenge.
PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
Shaoshuai Shi, Chaoxu Guo, Li Jiang, Zhe Wang, Jianping Shi, Xiaogang Wang, Hongsheng Li
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
[PDF]   [Bibtex]   [Code]   GitHub stars GitHub stars
Ranked 1st place on KITTI 3D object detection benchmark (Car, Nov-16 2019).
PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
Li Jiang, Hengshuang Zhao, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, Jiaya Jia
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Oral Presentation, 2020.
[PDF]   [Bibtex]   [Code]   GitHub stars
Ranked 1st place on ScanNet 3D Semantic instance benchmark (Nov-16 2019).
From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network
Shaoshuai Shi, Zhe Wang, Jianping Shi, Xiaogang Wang, Hongsheng Li
IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), accepted.
[PDF]   [Bibtex]   [Code]   GitHub stars GitHub stars
Ranked 1st place on KITTI 3D object detection benchmark (Car, July-9 2019).
PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud
Shaoshuai Shi, Xiaogang Wang, Hongsheng Li
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[PDF]   [Bibtex]   [Code]   GitHub stars
The top-10 cited papers among all CVPR-2019 papers (March, 2021), refer to here.
SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud
Hongwei Yi, Shaoshuai Shi, Mingyu Ding, Jiankai Sun, Kui Xu, Hui Zhou, Zhe Wang, Sheng Li, Guoping Wang
International Conference on Robotics and Automation (ICRA), 2020.
[PDF]   [Bibtex]  
Feature Intertwiner for Object Detection
Hongyang Li, Bo Dai, Shaoshuai Shi, Wanli Ouyang, Xiaogang Wang
International Conference on Learning Representation (ICLR), 2019.
[PDF]   [Bibtex]  
GAL: Geometric Adversarial Loss for Single-View 3D-Object Reconstruction
Li Jiang, Shaoshuai Shi, Xiaojuan Qi, Jiaya Jia
European Conference on Computer Vision (ECCV), Oral Presentation, 2018.
[PDF]   [Bibtex]  
FP-DNN: An automated framework for mapping deep neural networks onto FPGAs with RTL-HLS hybrid templates
Yijin Guan, Hao Liang, Ningyi Xu, Wenqiang Wang, Shaoshuai Shi, Xi Chen, Guangyu Sun, Wei Zhang, Jason Cong
IEEE Field-Programmable Custom Computing Machines (FCCM), 2017.
[PDF]   [Bibtex]  

Invited Talks


Education & Experiences


Honors & Awards