# sjtuytc/UnboundedNeRFPytorch

State-of-the-art, simple, fast unbounded / large-scale NeRFs.

Repository: https://github.com/sjtuytc/UnboundedNeRFPytorch
Canonical: https://ross.abutalabs.com/products/unboundednerfpytorch
Language: Python
License: MIT
License Family: permissive
Topics: nerf, pytorch-implementation, block-nerf, view-synthesis, weekly-nerf, classified, pytorch, chinese-translation, deep-learning, unbounded
Last push: 2024-06-11T09:29:03+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1506, "days_push": 813, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1324, forks 111 (observed 2026-08-28T04:04:22.415733+00:00)

## What it is
A PyTorch implementation benchmarking state-of-the-art unbounded (large-scale) neural radiance field methods like NeRF++, DVGO, and Block-NeRF. It provides a simple, fast codebase achieving SOTA PSNR on Mip-NeRF-360 and Tanks & Temples benchmarks.

## Use cases
- train unbounded NeRF models on large-scale scenes
- reproduce Mip-NeRF-360 benchmark results
- render novel views of outdoor 360-degree scenes
- benchmark radiance field algorithms like NeRF++ and DVGO
- train Block-NeRF style models on street-level imagery
- research large-scale neural radiance fields in PyTorch

## When to choose
- you need a simple, fast PyTorch codebase for unbounded/large-scale NeRFs
- you want SOTA-quality novel view synthesis on 360-degree outdoor scenes
- you want to benchmark multiple radiance field methods in one repo

## When to avoid
- you need a production-ready or well-supported library rather than a research project in progress
- you need bounded/indoor-only NeRF with a polished API
- you lack a GPU or PyTorch environment

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, graphics, simulation
- domain: computer-vision, graphics, deep-learning
- platform: python
- tags: nerf, neural-radiance-fields, view-synthesis, pytorch, block-nerf, mip-nerf-360, unbounded-scenes, research-code, research, gpu, linux

## Member repositories
- sjtuytc/UnboundedNeRFPytorch (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:22.415733+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 2026-08-30T04:47:01.918976+00:00, confidence not recorded.
  - readme: https://github.com/sjtuytc/UnboundedNeRFPytorch (fetched 2026-08-28T04:04:22.415733+00:00, sha 8b0a802e7e22)
- Data as of 2026-08-30T08:39:29.467469+00:00.