# yenchenlin/nerf-pytorch

A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

Repository: https://github.com/yenchenlin/nerf-pytorch
Canonical: https://ross.abutalabs.com/products/nerf-pytorch
Language: Python
License: MIT
License Family: permissive
Last push: 2024-07-25T10:27:44+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2341, "days_push": 769, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6044, forks 1122 (observed 2026-08-28T04:09:34.573785+00:00)

## What it is
A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the original paper's results for synthesizing novel views of complex scenes, running 1.3x faster than the authors' TensorFlow code. It includes example datasets, pre-trained models, and config-driven training scripts.

## Use cases
- train a NeRF model on synthetic or real image data
- generate novel views of a 3D scene from posed photographs
- reproduce NeRF paper results in PyTorch
- render spiral videos and depth maps of a scene
- learn how NeRF is implemented
- run NeRF on custom real-world captures with COLMAP poses

## When to choose
- you want a faithful, numerically verified PyTorch port of the original NeRF
- you need a simple, well-known reference implementation for research or education
- you have a CUDA GPU and want faster training than the original TensorFlow code

## When to avoid
- you need newer, faster NeRF variants like Instant-NGP or Mip-NeRF
- you need production-ready 3D reconstruction pipelines
- you have no GPU, since training takes hours even on a 2080 Ti

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, image-processing, graphics
- domain: computer-vision, deep-learning, graphics, machine-learning
- platform: python, windows
- tags: nerf, neural-radiance-fields, novel-view-synthesis, pytorch, 3d-reconstruction, research-code, gpu, linux, macos

## Member repositories
- yenchenlin/nerf-pytorch (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:34.573785+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:48:57.270757+00:00, confidence not recorded.
  - readme: https://github.com/yenchenlin/nerf-pytorch (fetched 2026-08-28T04:09:34.573785+00:00, sha 210b4a4d6f53)
- Data as of 2026-08-30T08:39:29.467469+00:00.