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 …

Abstract Three-dimensional (3D) human pose estimation involves estimating the articulated
3D joint locations of a human body from an image or video. Due to its widespread …

We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D
meshes generation from a single unposed image in the wild using both2D and 3D priors. In …

Estimating 3D human poses from monocular videos is a challenging task due to depth
ambiguity and self-occlusion. Most existing works attempt to solve both issues by exploiting …

Recent transformer-based solutions have been introduced to estimate 3D human pose from
2D keypoint sequence by considering body joints among all frames globally to learn spatio …

Human skeleton, as a compact representation of human action, has received increasing
attention in recent years. Many skeleton-based action recognition methods adopt GCNs to …

Transformer architectures have become the model of choice in natural language processing
and are now being introduced into computer vision tasks such as image classification, object …

Monocular 3D human pose estimation is quite challenging due to the inherent ambiguity
and occlusion, which often lead to high uncertainty and indeterminacy. On the other hand …

Unconditional human image generation is an important task in vision and graphics, enabling
various applications in the creative industry. Existing studies in this field mainly focus on …

In this paper, a novel Diffusion-based 3D Pose estimation (D3DP) method with Joint-wise
reProjection-based Multi-hypothesis Aggregation (JPMA) is proposed for probabilistic 3D …