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msracver/Deep-Image-Analogy

The source code of 'Visual Attribute Transfer through Deep Image Analogy'. observed · 2026-08-28

github.com/msracver/Deep-Image-Analogy · homepage · C++ · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3390
  • days_rel: n/a
  • days_push: 1801
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1370 stars · 230 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official C++/CUDA implementation of the SIGGRAPH 2017 'Visual Attribute Transfer through Deep Image Analogy' technique from Microsoft Research. It finds semantically meaningful dense correspondences between two images using CNN features to transfer color, texture, and style.

Use cases

  • transfer painting style to a photo
  • swap styles between two artworks
  • convert a sketch or painting into a photo
  • perform color and style swap between images
  • compute dense semantic correspondences between images
  • texture transfer between images

When to choose

  • you need semantically-aware style transfer that respects image structure, not just global texture
  • you want the reference implementation of the SIGGRAPH 2017 deep image analogy paper
  • you have an NVIDIA GPU and a Windows environment with CUDA 7.5/8

When to avoid

  • you need a maintained cross-platform or Python-friendly tool - it is only tested on Windows with old CUDA versions
  • your images are large - input is limited to roughly 700x500 pixels
  • you want modern deep-learning style transfer with active community support

Facets

library · maturity maintenance

image-processing computer-vision deep-learning computer-vision image-processing deep-learning windows cpp style-transfer cuda caffe image-analogy dense-correspondence siggraph-2017 gpu

6 sources

Member repositories

RepositoryRoleHealth v2
msracver/Deep-Image-Analogymain32

For agents

markdown · JSON · MCP: product_card(name="msracver/Deep-Image-Analogy")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem