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 …

Vision transformers are emerging as a powerful tool to solve computer vision problems.
Recent techniques have also proven the efficacy of transformers beyond the image domain …

Transformer models have shown great success handling long-range interactions, making
them a promising tool for modeling video. However, they lack inductive biases and scale …

Abstract Single Image Super-Resolution (SISR) is a crucial task in low-level computer vision
aiming to reconstruct high-resolution images from low-resolution counterparts. Conventional …

Gait recognition is beneficial for a variety of applications, including video surveillance, crime
scene investigation, and social security, to mention a few. However, gait recognition often …

Although action recognition systems can achieve top performance when evaluated on in-
distribution test points, they are vulnerable to unanticipated distribution shifts in test data …

In precision agriculture the detection and recognition of insects play an essential role in the
ability of crops to grow healthy and produce a high-quality yield. The current machine vision …

Visual interactivity understanding within visual scenes presents a significant challenge in
computer vision. Existing methods focus on complex interactivities while leveraging a simple …

Abstract Temporal Action Detection (TAD) aims to accurately capture each action interval in
an untrimmed video and to understand human actions. This paper comprehensively surveys …

Action recognition (AR) has many applications, including surveillance, health/disabilities
care, man‐machine interactions, video‐content‐based monitoring, and activity recognition …