Search Results for author:
Found 4 papers, 1 papers with code
PersonNeRF: Personalized Reconstruction from Photo Collections
We present PersonNeRF, a method that takes a collection of photos of a subject (e. g. Roger Federer) captured across multiple years with arbitrary body poses and appearances, and enables rendering the subject with arbitrary novel combinations of viewpoint, body pose, and appearance.
HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Video
Our method optimizes for a volumetric representation of the person in a canonical T-pose, in concert with a motion field that maps the estimated canonical representation to every frame of the video via backward warps.
Vid2Actor: Free-viewpoint Animatable Person Synthesis from Video in the Wild
At the core of our method is a volumetric 3D human representation reconstructed with a deep network trained on input video, enabling novel pose/view synthesis.
Photo Wake-Up: 3D Character Animation from a Single Photo
The key contributions of this paper are: 1) an application of viewing and animating humans in single photos in 3D, 2) a novel 2D warping method to deform a posable template body model to fit the person's complex silhouette to create an animatable mesh, and 3) a method for handling partial self occlusions.
