My research interests have revolved around human-centered visual computing, with the aim to build a machine that (1) technically reflect the depth characterized by human vision, (2) operate transparently, act equitably, respect the privacy, and (3) eventually amplify and augment human capabilities in diverse social challenges, e.g., healthcare.
I have received 1 Best Paper and 1 Outstanding Paper Nomination Awards. The research results in leading algorithms that won several international academic challenges held in conjunction with CVPR, ICCV, and industry challenges held by Alibaba.
New! Call for paper: Label-Efficient Learning on Video Data, Special Issue in IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 2022 (submission deadline: Apr. 1, 2023)
Tianfei Zhou, Fatih Porikli, David Crandall, Luc Van Gool, Wenguan Wang
IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2022, in press
Tianfei Zhou, Siyuan Qi, Wenguan Wang, Jianbing Shen, and Song-Chun Zhu
IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Computer Vision Laboratory
Biomedical Image Computing
ETF E 112
Senior Program Committee: AAAI'22
Guest Editor: IEEE TCSVT, Electronics
Conference Review: ICLR'22-23, NeurIPS'21-'23, ICML'22-23, CVPR, ICCV, ECCV, MICCAI, MIDL
Journal Review: IEEE TPAMI, IEEE TIP, MedIA, IEEE TMI, IJCV