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 …

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

To deal with the great number of untrimmed videos produced every day, we propose an
efficient unsupervised action segmentation method by detecting boundaries, named action …

We tackle real-world long-horizon robot manipulation tasks through skill discovery. We
present a bottom-up approach to learning a library of reusable skills from unsegmented …

This paper addresses a new problem of weakly-supervised online action segmentation in
instructional videos. We present a framework to segment streaming videos online at test time …

This work describes an end-to-end approach for real-time human action recognition from
raw depth image-sequences. The proposal is based on a 3D fully convolutional neural …

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 …

Temporal action segmentation tags action labels for every frame in an input untrimmed
video containing multiple actions in a sequence. For the task of temporal action …

Multimedia summarization with multimodal output can play an essential role in real-world
applications, ie, automatically generating cover images and titles for news articles or …

Temporal action segmentation is a task to classify each frame in the video with an action
label. However, it is quite expensive to annotate every frame in a large corpus of videos to …