I am currently a Ph.D student in Department of Computer Science at UNC at Chapel Hill, advised by Prof. Gedas Bertasius. My current research interests lie in computer vision. Specifically, I'm interested in video understanding, efficiency of video models and multi-modality.
Prior to joining Gedas's Group, I worked with Prof. Dinggang Shen and Prof. Pew-Thian Yap at UNC on medical imaging. I obtained both my B.S. degree in Information Security in 2016 and M.S. degree in ECE in 2019 at Shanghai JiaoTong University. During my M.S. study, I worked with Prof. Shilin Wang.
- 10/2022: Received a post-internship fellowship from Amazon.
TALLFormer: Temporal Action Localization with Long-memory Transformer
Feng Cheng, Gedas Bertasius
Preprint (accepted by ECCV2022) [Code]
Stochastic Backpropagation: A Memory Efficient Strategy for Training Video Models
Feng Cheng, Mingze Xu, Yuanjun Xiong, Hao Chen, Xinyu Li, Wei Li, Wei Xia
CVPR 2022 (Oral) [Code]
Spatio-Temporal Fusion based Convolutional Sequence Learning for Lip Reading
Xingxuan Zhang, Feng Cheng, and Shi-Lin Wang
Submillimeter 3D MR Fingerprinting with Whole-Brain Coverage via Dual-Domain Deep Learning Reconstruction
Feng Cheng, Yong Chen and Pew-Thian Yap
ISMRM 2021. (Oral, “magna cum laude” award)
Acceleration of High-Resolution 3D MR Fingerprinting via a Graph Convolutional Network
Feng Cheng, Yong Chen, Xiaopeng Zong, Weili Lin, Pew-Thian Yap,
Visual speaker authentication with random prompt texts by a dual-task CNN framework
Feng Cheng, Shi-Lin Wang, and Alan Wee-Chung Liew.
Pattern Recognition 2018
- 2022 /05 ~ 2022 /08 Applied Scientist Intern at Amazon AWS AI Mentor: Bing Shuai & Mingze Xu
- 2021 /05 ~ 2021 /08 Applied Scientist Intern at Amazon AWS AI Mentor: Mingze Xu & Yuanjun Xiong
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