Chengzhou Tang

About

I am currently a research scientist at Meta Reality Labs. 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 Adobe Research with Dr. Oliver Wang and Microsoft Research with Dr. Lu Yuan.

My research interests were computational photography, e.g. video stabilization, Structure-from-Motion & SLAM, and recently are combining classic optimization-based methods with deep learning for optical flow & stereo matching, image & video segmentation, etc.

Please refer to my CV for more details.

Contact

chengzhout@gmail.com

Updates

I am seeking faculty positions aiming to join in Fall 2024 or Spring 2025.
Please refer to my research statements and teaching statements .
Feel free to contact me directly regarding any available opportunities.

Publications

	Xiaodong Gu, Weihao Yuan, Zuozhuo Dai, Siyu Zhu, Chengzhou Tang, Zilong Dong, Ping Tan DRO: Deep Recurrent Optimizer for Video to Depth IEEE Robotics and Automation Letters. (RA-L), 2023 Paper
	Chengzhou Tang, Yuqiang Yang, Bing Zeng, Ping Tan, Shuaicheng Liu Learning to Zoom Inside Camera Imaging Pipeline IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Paper
	Xiaodong Gu,Chengzhou Tang, Weihao Yuan, Zuozhuo Dai, Siyu Zhu, Ping Tan RCP: Recurrent Closest Point for Scene Flow Estimation on 3D Point Clouds IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Paper
	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