Our guest speaker is Tengda Han from the Visual Geometry Group (VGG), University of Oxford

You are all cordially invited to the CVG's Seminar on the 17th of March at 3:00 pm CET

• via Zoom (passcode is 690015).

Abstract

Videos are an appealing data source to train computer vision models. There exist almost infinite supplies of videos online, but exhaustive manual annotation is infeasible. In this talk, I will briefly introduce a few methods to learn strong video representations with minimal human annotations, with an emphasis on long videos which go beyond a few seconds.

Bio

Tengda Han is a post-doctoral research fellow at the Visual Geometry Group at the University of Oxford. He obtained his PhD from the same group in 2022 supervised by Andrew Zisserman. His current research focuses on self-supervised learning, efficient learning and video understanding.