# How are MS-SSIM, LPIPS and FID defined and what input conventions do their original papers and reference code state?

- id: art_01M5MAT4GVQ5FR2S6VDPXCXE91
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T05, T20 · tags: none
- updated: 2026-10-23T12:12:15.224Z
- url: https://veyrul.com/articles/art_01M5MAT4GVQ5FR2S6VDPXCXE91

Comparing image-quality scores needs matched conventions: MS-SSIM's scale exponents come from an 8-subject calibration at 32 pixels per degree; LPIPS expects RGB tensors normalised to [-1,1] and asks users to state the version (0.1 current); pytorch-fid (same Inception weights as the TF reference) gives slightly different FID than the official TF code, and FID computed on non-default feature dims is not comparable with 2048-dim scores and may stop tracking visual quality.

Comparing image-quality scores needs matched conventions: MS-SSIM's scale exponents come from an 8-subject calibration at 32 pixels per degree; LPIPS expects RGB tensors normalised to [-1,1] and asks users to state the version (0.1 current); pytorch-fid (same Inception weights as the TF reference) gives slightly different FID than the official TF code, and FID computed on non-default feature dims is not comparable with 2048-dim scores and may stop tracking visual quality.

Curator qualifications: Papers/READMEs read 2026-10-22; no metric computed; no weights downloaded. FID paper (50,000-sample protocol) and LPIPS paper equation not re-read; producer reading. Network weights and BAPPS dataset terms not inspected.

Limitations: Papers/READMEs read 2026-10-22; no metric computed; no weights downloaded.

Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

```json
{
  "citations": [
    {
      "url": "https://arxiv.org/pdf/1706.08500v6",
      "note": "Wang, Simoncelli, Bovik, Multi-scale structural similarity (2003), Section 3.2 cross-scale calibration; LPIPS README at 082bb24 L19 and L96; LPIPS LICENSE at 082bb24; pytorch-fid README at b9c1811 L14, L41-55; pytorch-fid LICENSE at b9c1811"
    },
    {
      "url": "https://github.com/richzhang/PerceptualSimilarity/blob/082bb24f84c091ea94de2867d34c4544f68e0963/README.md",
      "note": "Wang, Simoncelli, Bovik, Multi-scale structural similarity (2003), Section 3.2 cross-scale calibration; LPIPS README at 082bb24 L19 and L96; LPIPS LICENSE at 082bb24; pytorch-fid README at b9c1811 L14, L41-55; pytorch-fid LICENSE at b9c1811"
    },
    {
      "url": "https://github.com/mseitzer/pytorch-fid/blob/b9c18118d082cbd263c1b8963fc4221dc1cbb659/README.md",
      "note": "Wang, Simoncelli, Bovik, Multi-scale structural similarity (2003), Section 3.2 cross-scale calibration; LPIPS README at 082bb24 L19 and L96; LPIPS LICENSE at 082bb24; pytorch-fid README at b9c1811 L14, L41-55; pytorch-fid LICENSE at b9c1811"
    },
    {
      "url": "https://www.cns.nyu.edu/pub/eero/wang03b.pdf",
      "note": "Wang, Simoncelli, Bovik, Multi-scale structural similarity (2003), Section 3.2 cross-scale calibration; LPIPS README at 082bb24 L19 and L96; LPIPS LICENSE at 082bb24; pytorch-fid README at b9c1811 L14, L41-55; pytorch-fid LICENSE at b9c1811"
    },
    {
      "url": "https://arxiv.org/pdf/1801.03924v2",
      "note": "Wang, Simoncelli, Bovik, Multi-scale structural similarity (2003), Section 3.2 cross-scale calibration; LPIPS README at 082bb24 L19 and L96; LPIPS LICENSE at 082bb24; pytorch-fid README at b9c1811 L14, L41-55; pytorch-fid LICENSE at b9c1811"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] Comparing image-quality scores needs matched conventions: MS-SSIM's scale exponents come from an 8-subject calibration at 32 pixels per degree; LPIPS expects RGB tensors normalised to [-1,1] and asks users to state the version (0.1 current); pytorch-fid (same Inception weights as the TF reference) gives slightly different FID than the official TF code, and FID computed on non-default feature dims is not comparable with 2048-dim scores and may stop tracking visual quality. · locator: Wang, Simoncelli, Bovik, Multi-scale structural similarity (2003), Section 3.2 cross-scale calibration; LPIPS README at 082bb24 L19 and L96; LPIPS LICENSE at 082bb24; pytorch-fid README at b9c1811 L14, L41-55; pytorch-fid LICENSE at b9c1811 · source: https://arxiv.org/pdf/1706.08500v6

Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=unknown training=unknown · Applies to this original summary only, not to the cited sources.

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