# xinntao/Real-ESRGAN

- id: src_01M569CK50GDY7GCYR1V1CCFAF
- type: source · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=metadata_checked, execution=not_run, review=unreviewed
- categories: T05 · tags: upscaling, super-resolution, restoration, anime, ncnn-vulkan, gfpgan, established, level:established
- updated: 2026-10-18T01:18:00.853Z
- url: https://veyrul.com/sources/src_01M569CK50GDY7GCYR1V1CCFAF

Source: https://github.com/xinntao/real-esrgan

```json
{
  "archived": false,
  "checked_at": "2026-10-17T00:00:00.000Z",
  "parent_url": null,
  "usefulness": "Long-standing practical image/video super-resolution toolkit trained on synthetic degradations, with general (x4plus, x2plus, general-x4v3), anime and anime-video models and portable ncnn-Vulkan executables that need no CUDA or PyTorch. The deterministic, low-hallucination upscaling baseline against which diffusion upscalers should be compared.",
  "source_type": "repository",
  "availability": "available",
  "dependencies": [
    "PyTorch>=1.7 or ncnn-vulkan",
    "basicsr",
    "facexlib",
    "gfpgan (face enhancement)"
  ],
  "source_owner": "Xintao Wang / Tencent ARC Lab",
  "next_check_at": "2026-11-16T00:00:00.000Z",
  "successor_url": null,
  "hardware_notes": "PyTorch route needs Python 3.7+ and PyTorch 1.7+; ncnn-Vulkan route needs no CUDA.",
  "known_limitations": [
    "Older GAN-based approach; will not synthesise new detail the way diffusion upscalers do.",
    "Uncertain maintenance."
  ],
  "upstream_updated_at": "2024-08-06T13:15:18.000Z"
}
```

Evidence claims:
- [sourced_fact] README lists realesr-general-x4v3, RealESRGAN_x4plus, x2plus, x4plus_anime_6B and AnimeVideo-v3 models plus a portable ncnn-Vulkan set for Windows/Linux/macOS running on Intel, AMD and Nvidia GPUs. · source: https://github.com/xinntao/Real-ESRGAN
- [inference] No archive banner on the page; about 37.1k stars, 587 open issues; portable executables tagged v0.2.5.0 with filenames dating to April 2022, so maintenance cadence appears low. · source: https://github.com/xinntao/Real-ESRGAN
- [sourced_fact] Limitations stated: ncnn executables lack some features (e.g. outscale), tiling can cause block inconsistencies, face enhancement requires extra packages (basicsr, facexlib, gfpgan). · source: https://github.com/xinntao/Real-ESRGAN
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.

Rights:
- code: license=BSD-3-Clause hosting=permitted redistribution=permitted modification=permitted training=unknown · Repo page labels BSD-3-Clause; weights-specific terms not stated on the fetched page. · evidence: https://github.com/xinntao/Real-ESRGAN
- model_weights: license=unknown hosting=unknown redistribution=unknown modification=unknown training=unknown · Pretrained model licensing not stated separately on the fetched README; training-data terms unknown. · evidence: https://github.com/xinntao/Real-ESRGAN

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