Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

Human action recognition and posture prediction aim to recognize and predict respectively
the action and postures of persons in videos. They are both active research topics in …

The pursuit of controllability as a higher standard of visual content creation has yielded
remarkable progress in customizable image synthesis. However, achieving controllable …

Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …

In the face of the video data deluge, today's expensive clip-level classifiers are increasingly
impractical. We propose a framework for efficient action recognition in untrimmed video that …

Abstract Weakly-supervised Temporal Action Localization (W-TAL) aims to classify and
localize all action instances in an untrimmed video under only video-level supervision …

This paper presents a pure transformer-based approach, dubbed the Multi-Modal Video
Transformer (MM-ViT), for video action recognition. Different from other schemes which …

Given an untrimmed video, temporal sentence grounding (TSG) aims to locate a target
moment semantically according to a sentence query. Although previous respectable works …

Deep 3D CNNs for video action recognition are designed to learn powerful representations
in the joint spatio-temporal feature space. In practice however, because of the large number …

Recently, 3D Convolutional Neural Network (3D CNN) models have been widely studied for
video sequences and achieved satisfying performance in action recognition and detection …