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 …

This paper introduces a unified framework for video action segmentation via sequence to
sequence (seq2seq) translation in a fully and timestamp supervised setup. In contrast to …

We present a new egocentric procedural error dataset containing videos with various types
of errors as well as normal videos and propose a new framework for procedural error …

Modeling long-term context in videos is crucial for many fine-grained tasks including
temporal action segmentation. An interesting question that is still open is how much long …

We study supervised action segmentation whose goal is to predict framewise action labels
of a video. To capture temporal dependencies over long horizons prior works either improve …

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

Temporal action segmentation approaches have been very successful recently. However,
annotating videos with frame-wise labels to train such models is very expensive and time …

We present a novel method for weakly-supervised action segmentation and unseen error
detection in anomalous instructional videos. In the absence of an appropriate dataset for this …

Action segmentation refers to inferring boundaries of semantically consistent visual concepts
in videos and is an important requirement for many video understanding tasks. For this and …

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 …