Collection of resources around NeRF. From total noob to recently released papers.
This repo aims at giving a view of all actors and technics around NeRF: papers, repo, people, companies, etc
PR accepted!
A curated list of awesome scene representation(NeRFs) papers, code, and resources. https://github.com/pixel-alex/awesome-scene-representation
A repo collating papers and other material related to neural radiance fields (NeRFs), neural scene representations and associated works with a focus towards applications in robotics. https://github.com/RoboticImaging/neural_fields_for_robotics_resources
Awesome NeRF (Huge collection) https://github.com/awesome-NeRF/awesome-NeRF
Why THIS is the Future of Imagery. Introduction video made my VFX artists. https://www.youtube.com/watch?v=YX5AoaWrowY
Understanding and Extending Neural Radiance Fields. High level explanation from 2D neural representation to 3D https://www.youtube.com/watch?v=HfJpQCBTqZs
Neural Radiance Fields for Unconstrained Photo Collections https://nerf-w.github.io/
3D Gaussian Splatting for Real-Time Radiance Field Rendering https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/
Random-Access Neural Compression of Material Textures https://research.nvidia.com/labs/rtr/neural_texture_compression/ Associated Twitter thread here : https://twitter.com/BartWronsk/status/1653445678268575744
NeRF - Representing Scenes as Neural Radiance Fields for View Synthesis (2020) https://www.matthewtancik.com/nerf
Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields https://jonbarron.info/zipnerf/
Multi-Space Neural Radiance Fields https://zx-yin.github.io/msnerf/
HumanRF: High-Fidelity Neural Radiance Fields for Humans in Motion https://synthesiaresearch.github.io/humanrf/
Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields https://eckertzhang.github.io/Text2NeRF.github.io/?s=03
NeRF-Texture: Texture Synthesis with Neural Radiance Fields https://yihua7.github.io/NeRF-Texture-web/
a pytorch implementation for the paper: TensoRF: Tensorial Radiance Fields. Our work present a novel approach to model and reconstruct radiance fields, which achieves super fast training process, compact memory footprint and state-of-the-art rendering quality. https://github.com/grgkopanas/TensoRF
NeRF++: Analyzing and Improving Neural Radiance Fields https://github.com/grgkopanas/nerfplusplus
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding https://github.com/NVlabs/instant-ngp Related paper here : https://nvlabs.github.io/instant-ngp/assets/mueller2022instant.pdf
Jon Barron, a senior staff research scientist at Google Research in San Francisco. https://jonbarron.info/
Luma AI - NeRF mobile capture app https://lumalabs.ai/
In audio processing, this technique has been applied to acoustic and head-related transfer function interpolation. https://arxiv.org/abs/2305.04447