# leehomyc/Faster-High-Res-Neural-Inpainting

High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis

Repository: https://github.com/leehomyc/Faster-High-Res-Neural-Inpainting
Canonical: https://ross.abutalabs.com/products/faster-high-res-neural-inpainting
Homepage: http://www.harryyang.org/inpainting
Language: Lua
License: MIT
License Family: permissive
Topics: deep-learning, deep-learning-papers, machine-learning
Last push: 2018-05-29T22:01:59+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": 3506, "days_push": 3018, "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 1286, forks 207 (observed 2026-08-28T04:04:14.890569+00:00)

## What it is
Research code implementing the CVPR 2017 paper 'High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis', written in Lua for the Torch framework. It fills in missing regions of images using a content network plus texture optimization, with pre-trained models and demo scripts included.

## Use cases
- fill in missing or masked regions of high-resolution images
- remove unwanted objects from photos using neural inpainting
- reproduce CVPR 2017 multi-scale neural patch synthesis results
- run image inpainting experiments with pre-trained Torch models
- photo editing via content-aware fill

## When to choose
- you need to reproduce or build on this specific CVPR 2017 inpainting paper
- you work in Torch/Lua and want a research-grade inpainting implementation
- you want high-resolution inpainting with texture optimization rather than a quick GAN fill

## When to avoid
- you need a maintained, production-ready inpainting tool
- your stack is PyTorch or TensorFlow rather than Torch/Lua
- you need fast real-time inpainting (original version took ~30s/image even after 6x speedup)

## Facets
- artifact type: library
- maturity: abandoned
- function: image-processing, deep-learning, machine-learning
- domain: computer-vision, image-processing, deep-learning, machine-learning
- platform: lua
- tags: image-inpainting, torch, research-code, cvpr-paper, neural-patch-synthesis, gpu, linux

## Member repositories
- leehomyc/Faster-High-Res-Neural-Inpainting (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:14.890569+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 2026-08-30T04:56:35.377496+00:00, confidence not recorded.
  - readme: https://github.com/leehomyc/Faster-High-Res-Neural-Inpainting (fetched 2026-08-28T04:04:14.890569+00:00, sha 8568c93b67f1)
  - homepage: http://www.harryyang.org/inpainting (fetched 2026-08-29T12:12:41.784572+00:00, sha a9a9bbe4aea9)
- Data as of 2026-08-30T08:39:29.467469+00:00.