Chengzhou Tang

About

I am currently a research scientist at Meta AI Applied Research. I got my doctoral degree from Simon Fraser University, supervised by Prof. Ping Tan. I had the the honor of working as research interns at Microsoft Research with Dr. Lu Yuan and at Adobe Research with Dr. Oliver Wang.

My research interests are video stabilization, structure-from-motion & SLAM, and recently combining classic model based methods with deep learning for optical flow, interactive segmentation, etc.

Please refer to my CV for more details.

Contact

chengzhou_tang@sfu.ca (will be expired soon) or chengzhout@gmail.com

Publications

	Shitao Tang,Chengzhou Tang, Rui Huang, Siyu Zhu, and Ping Tan DSM: Dense Scene Matching for Camera Localization IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Paper Code
	Chengzhou Tang, Lu Yuan, and Ping Tan LSM: Learning Subspace Minmization for Low-level Vision IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Oral Presentation (5% acceptance rate), 2020 Paper Code
	Luwei Yang, Ziqian Bai, Chengzhou Tang, Honghua Li, Yasutaka Furukawa, and Ping Tan SANet: Scene Agnostic Network for Camera Localization International Conference on Computer Vision (ICCV), 2019 Paper Code
	Chengzhou Tang and Ping Tan BA-Net: Dense Bundle Adjustment Networks International Conference on Learning Representations (ICLR), Oral Presentation (1.7% acceptance rate), 2019 Paper Code
	Chengzhou Tang, Oliver Wang, Feng Liu and Ping Tan Joint Direction and Stabilization for 360° Videos ACM Transactions on Graphics (TOG), Presented at SIGGRAPH 2019 Paper Code(comming soon)
	Chengzhou Tang, Oliver Wang and Ping Tan GSLAM: Intialization-robust Monocular SLAM via Global Structure-from-Motion International Conference on 3D Vision (3DV), 2017 Paper Code
	Zhaopeng Cui, Nianjuan Jiang, Chengzhou Tang and Ping Tan Linear Global Translation Estimation with Feature Tracks British Machine Vision Conference (BMVC), 2015 Paper
	Chengzhou Tang and Ronggang Wang Local Subspace Video Stabilization IEEE International Conference on Multimedia and Expo (ICME), 2014 Paper
	Chengzhou Tang and Ronggang Wang Sparse Moving Factorization for Subspace Video Stabilization IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014 Paper
	Chengzhou Tang,Ronggang Wang, and Wenmin Wang Adaptive Motion Estimation Order for Frame Rate Up-conversion IEEE International Symposium on Circuits and Systems (ISCAS), 2013 Paper

Reviwers

Computer Vision: CVPR, ECCV, ICCV, WACV; IJCV, TPAMI, MVA
Machine Learning: NeurIPS, ICML, ICLR, AAAI
Graphics: PG, IEEE VR, VRST; TVCG, CGF
Robotics: IROS, ICRA; AUTON ROBOT