# vsitzmann/awesome-implicit-representations

A curated list of resources on implicit neural representations.

Repository: https://github.com/vsitzmann/awesome-implicit-representations
Canonical: https://ross.abutalabs.com/products/awesome-implicit-representations
License: MIT
License Family: permissive
Last push: 2024-02-11T22:48:44+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": 2074, "days_push": 934, "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 2648, forks 147 (observed 2026-08-28T04:07:06.867908+00:00)

## What it is
A curated awesome-list of papers, talks, and Colabs on implicit neural representations (coordinate-based networks like SIREN and neural scene representations). It serves as a reading guide for researchers entering the field.

## Use cases
- find papers on implicit neural representations
- learn about neural fields and coordinate-based networks
- get a reading list for neural scene representations
- find tutorials and colabs on SIREN and NeRF-style models
- survey research on neural rendering and signed distance functions

## When to choose
- you want a curated, opinionated reading list on implicit neural representations
- you are a student or researcher starting out in neural fields
- you want foundational papers plus talks and notebooks in one place

## When to avoid
- you need an exhaustive, frequently updated index of every paper in the field
- you want runnable production software rather than references
- you expect pull requests adding new papers to be merged

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, machine-learning, computer-vision, graphics
- domain: deep-learning, computer-vision, graphics, tutorials
- platform: cross-platform
- tags: awesome-list, implicit-neural-representations, neural-rendering, neural-fields, research-papers, curated-list

## Member repositories
- vsitzmann/awesome-implicit-representations (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:06.867908+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 2026-08-30T02:18:56.582049+00:00, confidence not recorded.
  - readme: https://github.com/vsitzmann/awesome-implicit-representations (fetched 2026-08-28T04:07:06.867908+00:00, sha 1862976b2027)
- Data as of 2026-08-30T08:39:29.467469+00:00.