How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
This project is a computer vision pipeline and volumetric rendering system used to transform photos and videos into high-fidelity 3D models. It implements a deformable neural radiance field framework that optimizes deformation fields to represent non-rigid moving subjects in three dimensions. The system utilizes volumetric deformation fields to map 3D coordinates from a static canonical space to a deformed state. This allows for the reconstruction of photorealistic scenes and the synthesis of high-fidelity images from camera perspectives not present in the original input data. The framework
Code for "HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields".
This is the code for Deformable Neural Radiance Fields, a.k.a. Nerfies.
Dynamic Neural Radiance Fields for Monocular 4D Facial Avater Reconstruction
HumanNeRF turns a monocular video of moving people into a 360 free-viewpoint video.
The main features of chungyiweng/humannerf are: Deformable Scenes.
Projects with overlapping indexed features include: nerfies/nerfies.github.io — This project is a computer vision pipeline and volumetric rendering system used to transform photos and videos into… gafniguy/4d-facial-avatars — Dynamic Neural Radiance Fields for Monocular 4D Facial Avater Reconstruction. google/hypernerf — Code for "HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields". google/nerfies — This is the code for Deformable Neural Radiance Fields, a.k.a. Nerfies. googleinterns/ibrnet — PyTorch implementation of paper "IBRNet: Learning Multi-View Image-Based Rendering", CVPR 2021. hustvl/tineuvox — TiNeuVox: Fast Dynamic Radiance Fields with Time-Aware Neural Voxels (SIGGRAPH Asia 2022).