# snap-research/NeROIC

Repository: https://github.com/snap-research/NeROIC
Canonical: https://ross.abutalabs.com/products/neroic
Language: Python
License: NOASSERTION
License Family: other
Last push: 2023-01-19T22:21:36+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1699, "days_push": 1322, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1012, forks 132 (observed 2026-08-28T04:03:13.420150+00:00)

## What it is
Official PyTorch implementation of NeROIC, a neural method for capturing 3D object geometry and material from online image collections and rendering novel views with relighting. It trains geometry and rendering networks in stages from multi-view images.

## Use cases
- reconstruct 3d objects from photos
- novel view synthesis of an object
- relight a captured 3d object
- decompose materials from images
- neural object capture from online images

## When to choose
- you need research-grade neural 3D object capture from multi-view images
- you want to reproduce the NeROIC paper results
- you need relighting or material decomposition of captured objects

## When to avoid
- you need a production-ready 3D scanning pipeline
- you lack GPU resources for multi-stage training
- you need Windows or macOS support without adaptation

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

## Member repositories
- snap-research/NeROIC (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:13.420150+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 2026-08-30T07:11:47.596786+00:00, confidence not recorded.
  - readme: https://github.com/snap-research/NeROIC (fetched 2026-08-28T04:03:13.420150+00:00, sha d9b4f47db27a)
- Data as of 2026-08-30T08:39:29.467469+00:00.