Recovering 3d human mesh from monocular images: A survey
Estimating human pose and shape from monocular images is a long-standing problem in
computer vision. Since the release of statistical body models, 3D human mesh recovery has …
computer vision. Since the release of statistical body models, 3D human mesh recovery has …
FastViT: A fast hybrid vision transformer using structural reparameterization
The recent amalgamation of transformer and convolutional designs has led to steady
improvements in accuracy and efficiency of the models. In this work, we introduce FastViT, a …
improvements in accuracy and efficiency of the models. In this work, we introduce FastViT, a …
Pymaf-x: Towards well-aligned full-body model regression from monocular images
We present PyMAF-X, a regression-based approach to recovering a parametric full-body
model from a single image. This task is very challenging since minor parametric deviation …
model from a single image. This task is very challenging since minor parametric deviation …
Frankmocap: A monocular 3d whole-body pose estimation system via regression and integration
Most existing monocular 3D pose estimation approaches only focus on a single body part,
neglecting the fact that the essential nuance of human motion is conveyed through a concert …
neglecting the fact that the essential nuance of human motion is conveyed through a concert …
Interacting attention graph for single image two-hand reconstruction
Graph convolutional network (GCN) has achieved great success in single hand
reconstruction task, while interacting two-hand reconstruction by GCN remains unexplored …
reconstruction task, while interacting two-hand reconstruction by GCN remains unexplored …
Monocular expressive body regression through body-driven attention
To understand how people look, interact, or perform tasks, we need to quickly and
accurately capture their 3D body, face, and hands together from an RGB image. Most …
accurately capture their 3D body, face, and hands together from an RGB image. Most …
Handoccnet: Occlusion-robust 3d hand mesh estimation network
Hands are often severely occluded by objects, which makes 3D hand mesh estimation
challenging. Previous works often have disregarded information at occluded regions …
challenging. Previous works often have disregarded information at occluded regions …
A dataset of relighted 3D interacting hands
The two-hand interaction is one of the most challenging signals to analyze due to the self-
similarity, complicated articulations, and occlusions of hands. Although several datasets …
similarity, complicated articulations, and occlusions of hands. Although several datasets …
Reconstructing hands in 3d with transformers
We present an approach that can reconstruct hands in 3D from monocular input. Our
approach for Hand Mesh Recovery HaMeR follows a fully transformer-based architecture …
approach for Hand Mesh Recovery HaMeR follows a fully transformer-based architecture …
Dexmv: Imitation learning for dexterous manipulation from human videos
While significant progress has been made on understanding hand-object interactions in
computer vision, it is still very challenging for robots to perform complex dexterous …
computer vision, it is still very challenging for robots to perform complex dexterous …