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 …

Temporally locating and classifying action segments in long untrimmed videos is of
particular interest to many applications like surveillance and robotics. While traditional …

Deep neural networks (DNNs) have recently achieved great success in many visual
recognition tasks. However, existing deep neural network models are computationally …

With the success of deep learning in classifying short trimmed videos, more attention has
been focused on temporally segmenting and classifying activities in long untrimmed videos …

This paper addresses the problem of temporal sentence grounding (TSG), which aims to
identify the temporal boundary of a specific segment from an untrimmed video by a sentence …

Abstract Person Re-Identification (person re-id) is a crucial task as its applications in visual
surveillance and human-computer interaction. In this work, we present a novel joint Spatial …

Temporal relations among multiple action segments play an important role in action
segmentation especially when observations are limited (eg, actions are occluded by other …

While current approaches to action recognition on pre-segmented video clips already
achieve high accuracies, temporal action detection is still far from comparably good results …

Temporal receptive fields of models play an important role in action segmentation. Large
receptive fields facilitate the long-term relations among video clips while small receptive …

We describe an end-to-end generative approach for the segmentation and recognition of
human activities. In this approach, a visual representation based on reduced Fisher Vectors …