CVPR 2023
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2nd Workshop on Federated Learning for Computer Vision

Chen Chen · Salman Avestimehr · Zhengming Ding · Mi Zhang · Ravikumar Balakrishnan · Nageen Himayat · Ang Li · Lingjuan Lyu · Naji Khosravan · Seyyedali Hosseinalipour · Lichao Sun

West 217 - 219

Mon 19 Jun, 8:30 a.m. PDT

Keywords:  Learning  

Federated Learning (FL) has become an important privacy-preserving paradigm in various machine learning tasks. However, the potential of FL in computer vision applications, such as face recognition, person re-identification, and action recognition, is far from being fully exploited. Moreover, FL has rarely been demonstrated effectively in advanced computer vision tasks such as object detection and image segmentation, compared to the traditional centralized training paradigm. This workshop aims at bringing together researchers and practitioners with common interests in FL for computer vision and studying the different synergistic relations in this interdisciplinary area. The day-long event will facilitate interaction among students, scholars, and industry professionals from around the world to discuss future research challenges and opportunities.

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