22 open-source projects similar to googleinterns/ibrnet, ranked by shared indexed features. Tags may describe platforms or build tools rather than the same primary purpose. Check each project’s use case, license, and deployment requirements before treating it as a replacement.
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
ICCV 2021 Our work presents a novel neural rendering approach that can efficiently reconstruct geometric and neural radiance fields for view synthesis.
Official code release for "GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis"
HumanNeRF turns a monocular video of moving people into a 360 free-viewpoint video.
Dynamic Neural Radiance Fields for Monocular 4D Facial Avater Reconstruction
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.
WACV 2023 XNeRF: Explicit Neural Radiance Field for Multi-Scene 360° Insufficient RGB-D Views
TiNeuVox: Fast Dynamic Radiance Fields with Time-Aware Neural Voxels (SIGGRAPH Asia 2022)
CVPR 2024 🏡Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language Reasoning
Matthew Tancik\ 1 , Ben Mildenhall\ 1 , Terrance Wang 1 , Divi Schmidt 1 , Pratul P. Srinivasan 2 , Jonathan T. Barron 2 , Ren Ng 1
Code and models for our ICCV 2021 paper "MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis"
ECCV 2022 "SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image", Dejia Xu, Yifan Jiang, Peihao Wang, Zhiwen Fan, Humphrey Shi, Zhangyang Wang
Point-NeRF: Point-based Neural Radiance Fields
CVPR 2024 Official code release for "UFORecon: Generalizable Sparse-View Surface Reconstruction from Arbitrary and UnFavOrable Sets"
PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes"
D-NeRF is a method for synthesizing novel views, at an arbitrary point in time, of dynamic scenes with complex non-rigid geometries. We optimize an underlying deformable volumetric function from a sparse set of input monocular views without the need of ground-truth geometry nor multi-view images.
Pytorch code for ICCV'23 paper. NEO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes