Temporal action segmentation (TAS) in videos aims at densely identifying video frames in
minutes-long videos with multiple action classes. As a long-range video understanding task …

Recent advances in transformer-based models have drawn attention to exploring these
techniques in medical image segmentation, especially in conjunction with the U-Net model …

We address the problem of online action segmentation for egocentric procedural task
videos. While previous studies have mostly focused on offline action segmentation where …

Estimating the 2D human poses in each view is typically the first step in calibrated multi-view
3D pose estimation. But the performance of 2D pose detectors suffers from challenging …

We aim to learn to temporally localize object state changes and the corresponding state-
modifying actions by observing people interacting with objects in long uncurated web …

The aim of weakly supervised object co-localization is to locate different objects of the same
superclass in a dataset. Recent methods achieve impressive co-localization performance by …

We aim to learn to temporally localize object state changes and the corresponding state-
modifying actions by observing people interacting with objects in long uncurated web …

We aim to learn to temporally localize object state changes and the corresponding state-
modifying actions by observing people interacting with objects in long uncurated web …

This paper presents an unsupervised transformer-based framework for temporal activity
segmentation which leverages not only frame-level cues but also segment-level cues. This …

In this paper, we propose a novel fully unsupervised framework that learns action
representations suitable for the action segmentation task from the single input video itself …