Towards Long-Form Video Understanding

Code

• github.com/chaoyuaw/lvu
  OfficialIn paperpytorch★ 87
• github.com/md-mohaiminul/ViS4mer
  pytorch★ 58

Abstract

Our world offers a never-ending stream of visual stimuli, yet today's vision systems only accurately recognize patterns within a few seconds. These systems understand the present, but fail to contextualize it in past or future events. In this paper, we study long-form video understanding. We introduce a framework for modeling long-form videos and develop evaluation protocols on large-scale datasets. We show that existing state-of-the-art short-term models are limited for long-form tasks. A novel object-centric transformer-based video recognition architecture performs significantly better on 7 diverse tasks. It also outperforms comparable state-of-the-art on the AVA dataset.

Tasks

Benchmark Results

Reproductions