My name is Min-Hung (Steve) Chen (陳敏弘 in Chinese). I am a Senior Research Scientist at NVIDIA Research Taiwan, working on Vision+X Multi-Modal AI. I received my Ph.D. degree from Georgia Tech, advised by Prof. Ghassan AlRegib and in collaboration with Prof. Zsolt Kira. Before joining NVIDIA, I was working on Biometric Research for Cognitive Services as a Research Engineer II at Microsoft Azure AI, and was working on Edge-AI Research as a Senior AI Engineer at MediaTek, respectively.
My research interest is mainly Multi-Modal AI, including Vision-Language, Video Understanding, Cross-Modal Learning, Efficient Tuning, and Transformer. I am also interested in Learning without Fully Supervision, including domain adaptation, transfer learning, continual learning, X-supervised learning, etc.
[Recruiting] NVIDIA Taiwan is hiring Research Scientist (fulltime & internship). I am also open to research collaboration. Please drop me an email if you are interested in.
PhD in Electrical and Computer Engineering, 2020
Georgia Institute of Technology
MSc in Integrated Circuits and Systems, 2012
National Taiwan University
BSc in Electrical Engineering, 2010
National Taiwan University
An ultimately comprehensive paper list of Vision Transformer and Attention, including papers, codes, and related websites.
Deep Learning and Computer Vision system for real-time autonomous retail stores using only RGB cameras.
The Learned Smartphone ISP Challenge for the CVPR 2021 MAI Workshop.
Cross-domain action segmentation by aligning temporal feature spaces.
Two methods (TS-LSTM and Temporal-Inception) to exploit spatiotemporal dynamics for activity recognition.
Cross-domain action recognition with new datasets and novel video-based DA approaches.
A large-scale traffic sign detection dataset with various challenging conditions.
[CVPR 2020] Cross-domain action segmentation by aligning feature spaces across multiple temporal scales with self-supervised learning to reduce spatio-temporal variability.
[ICCV 2019 (Oral)] Cross-domain action recognition with new datasets and novel attention-based DA approaches.
Graduate Teaching Assistant