Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

Estimation of the human pose from a monocular camera has been an emerging research
topic in the computer vision community with many applications. Recently, benefiting from the …

Vision transformers have achieved great successes in many computer vision tasks. Most
methods generate vision tokens by splitting an image into a regular and fixed grid and …

Abstract Spiking Neural Networks (SNNs) have gained huge attention as a potential energy-
efficient alternative to conventional Artificial Neural Networks (ANNs) due to their inherent …

In this paper, we introduce a novel visual representation learning which relies on a handful
of adaptively learned tokens, and which is applicable to both image and video …

Human pose estimation (HPE) has attracted a significant amount of attention from the
computer vision community in the past decades. Moreover, HPE has been applied to various …

While the voxel-based methods have achieved promising results for multi-person 3D pose
estimation from multi-cameras, they suffer from heavy computation burdens, especially for …

Deep neural networks have rapidly become the mainstream method for face recognition
(FR). However, this limits the deployment of such models that contain an extremely large …

This paper investigates the task of 2D whole-body human pose estimation, which aims to
localize dense landmarks on the entire human body including body, feet, face, and hands …

Existing works on 2D pose estimation mainly focus on a certain category, eg human, animal,
and vehicle. However, there are lots of application scenarios that require detecting the …