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Found 6 papers, 1 papers with code
ShapeGraFormer: GraFormer-Based Network for Hand-Object Reconstruction from a Single Depth Map
In addition, we show the impact of adding another GraFormer component that refines the reconstructed shapes based on the hand-object interactions and its ability to reconstruct more accurate object shapes.
THOR-Net: End-to-end Graformer-based Realistic Two Hands and Object Reconstruction with Self-supervision
In the features extraction stage, a Keypoint RCNN is used to extract 2D poses, features maps, heatmaps, and bounding boxes from a monocular RGB image.
Model-based Outdoor Performance Capture
We propose a new model-based method to accurately reconstruct human performances captured outdoors in a multi-camera setup.
General Automatic Human Shape and Motion Capture Using Volumetric Contour Cues
Our method uses a new image formation model with analytic visibility and analytically differentiable alignment energy.
A Versatile Scene Model with Differentiable Visibility Applied to Generative Pose Estimation
Generative reconstruction methods compute the 3D configuration (such as pose and/or geometry) of a shape by optimizing the overlap of the projected 3D shape model with images.
Efficient Multi-view Performance Capture of Fine-Scale Surface Detail
We present a new effective way for performance capture of deforming meshes with fine-scale time-varying surface detail from multi-view video.
