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 …

Deep neural networks have become prevalent in human analysis, boosting the performance
of applications, such as biometric recognition, action recognition, as well as person re …

We introduce TADA, a simple-yet-effective approach that takes textual descriptions and
produces expressive 3D avatars with high-quality geometry and lifelike textures, that can be …

Gaussian splatting has emerged as a powerful 3D representation that harnesses the
advantages of both explicit (mesh) and implicit (NeRF) 3D representations. In this paper we …

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 …

Constructing and animating humans is an important component for building virtual worlds in
a wide variety of applications such as virtual reality or robotics testing in simulation. As there …

We propose a Transformer-based framework for 3D human texture estimation from a single
image. The proposed Transformer is able to effectively exploit the global information of the …

TV shows depict a wide variety of human behaviors and have been studied extensively for
their potential to be a rich source of data for many applications. However, the majority of the …

Animals are capable of extreme agility, yet understanding their complex dynamics, which
have ecological, biomechanical and evolutionary implications, remains challenging. Being …

Human pose is a useful feature for fine-grained sports action understanding. However, pose
estimators are often unreliable when run on sports video due to domain shift and factors …