Merge remote-tracking branch 'origin/main' into docs/arxiv-paper-review

# Conflicts:
#	docs/installation.md
#	docs/supported-signals.md
#	docs/verification-plan.md
This commit is contained in:
Victor Kuznetsov
2026-08-28 11:18:08 -07:00
122 changed files with 2634 additions and 456 deletions
+88 -19
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@@ -296,13 +296,13 @@ from the gate. The full-clip oracle floor is
detected while `0.15` did not.
[`video_visible.py`](../src/remove_ai_watermarks/video_visible.py) implements
the first pixel stages for Sora, Veo, Seedance, Dola, Hailuo, and Kling. The
the first pixel stages for Sora, Veo, Seedance, Dola, Hailuo AI, and Kling AI. The
Sora detector searches a normalized frame with a fully synthetic
mascot-and-text silhouette at several scales. The Veo detector uses separate
synthetic silhouettes for the current four-point diamond and legacy `Veo`
text. Seedance uses a synthetic rounded boxed-`AI` silhouette, while Dola uses
an OpenCV-font `Dola AI` silhouette. Hailuo uses a synthetic waveform,
MINIMAX/Hailuo text, separator, and ring. Kling combines synthetic font
an OpenCV-font `Dola AI` silhouette. Hailuo AI uses a synthetic waveform,
MINIMAX/Hailuo AI text, separator, and ring. Kling AI combines synthetic font
variants with a ring approximation of its swirl; the logo path rescues
wordmarks whose version or font differs, while the edge and white-label gates
reject recurring scene texture. All fixed-mark searches are bounded to the
@@ -323,23 +323,23 @@ Every per-frame result is untrusted. Each provider's floors, minimum-run policy,
fill padding and mask style are one row in `VISIBLE_MARK_POLICIES`, and every mark
enters the same `stabilize_localizations` entry point; the recurrence
implementation underneath knows nothing about providers. That policy row also
carries `accepts_provenance`, which forces `provenance=False` for Hailuo and Kling
carries `accepts_provenance`, which forces `provenance=False` for Hailuo AI and Kling AI
— they have no metadata that could confirm them, and the guarantee used to be
structural (their wrappers took no `provenance` parameter at all). Provenance can relax a low-contrast run only
after recurring visual evidence exists. Sora transition frames follow the
nearest confirmed moving position only with Sora provenance. Seedance, Dola,
Hailuo, and Kling additionally require candidates to remain anchored to the
Hailuo AI, and Kling AI additionally require candidates to remain anchored to the
start of a run. This rejects slowly drifting scene details that still have
high frame-to-frame overlap. Hailuo and Kling do not infer provenance from
high frame-to-frame overlap. Hailuo AI and Kling AI do not infer provenance from
technical encoder tags; their confirmed public samples carried no provider
metadata.
Removal runs in a second decode pass. Sora, legacy Veo text, Dola text,
Seedance, Hailuo, and Kling use box masks. Seedance deliberately fills the
Seedance, Hailuo AI, and Kling AI use box masks. Seedance deliberately fills the
complete localized box: a synthetic outline mask passed repeat detection but
left part of the real translucent border visible during visual end-to-end
review. Hailuo expands beyond the matched core to cover both provider icons.
Kling expands around the wordmark or swirl to include the version and optional
review. Hailuo AI expands beyond the matched core to cover both provider icons.
Kling AI expands around the wordmark or swirl to include the version and optional
`PRO` suffix. The square Veo diamond uses a synthetic shape mask so transparent
corners do not erase unrelated pixels. Every mask goes through the shared
`watermark_registry.fill` backends. ffmpeg encodes the changed video stream and
@@ -451,7 +451,9 @@ For an AI C2PA claim, a recognized product in `claim_generator` takes precedence
over the certificate issuer: an application can sign through an upstream model
provider without becoming that provider's product. Only exact product mappings
receive this precedence; an unknown claim generator still falls back to issuer
attribution.
attribution. An unmapped issuer org reads as unknown-signer C2PA with no platform;
that is how Ideogram was surfaced (4 corpus uploads signed "Ideogram, Inc",
2026-08-08) before its vendor row was added on 2026-08-27.
### Metadata scanning and stripping
@@ -1121,9 +1123,9 @@ capture-less pill is too weak to attribute.
The set of marks that veto the pill is DERIVED from the registry rows: every mark
under the same label regime (`tc260`) belonging to a different product. It used to
be a hand-written list of keys, and that list drifted -- LibLibAI was registered
alongside RunningHub and Baidu, both of which were added to it, and LibLibAI was
not, so a confident LibLibAI detection did not suppress the pill the way its two
be a hand-written list of keys, and that list drifted -- LiblibAI was registered
alongside RunningHub and Baidu, both of which were added to it, and LiblibAI was
not, so a confident LiblibAI detection did not suppress the pill the way its two
siblings did. Marks outside the TC260 regime (Gemini, Samsung) are deliberately
not vetoers: neither can put `jimeng` into `provenance`, so neither can enable the
arm it would be vetoing.
@@ -1175,6 +1177,33 @@ be represented by the shared base:
- [`runninghub_engine.py`](../src/remove_ai_watermarks/runninghub_engine.py)
- [`baidu_engine.py`](../src/remove_ai_watermarks/baidu_engine.py)
- [`liblib_engine.py`](../src/remove_ai_watermarks/liblib_engine.py)
- [`microsoft_engine.py`](../src/remove_ai_watermarks/microsoft_engine.py)
The measured Microsoft badge variant (2026-08-27 registration) is the first
`tr`-corner mark and the first `long`-side scale basis: the pill tracks the
render dimension, so a
1024x1536 portrait carries the same pill as 1536x1024, and a width basis
undersized the template by the aspect ratio (portrait carriers fell to
0.15-0.32 NCC until the basis was measured). The silhouette is a white pill with
its synthetic internal shapes knocked out - the holes are what separate it from
any other bright rounded corner element (a plain white pill scores below the gate
in the tests). It does not claim coverage of Microsoft's other documented icon,
wording, or position variants.
The 2026-08-27 rerun used the registered engine through
`scripts/registered_mark_calibrate.py`, rather than a copied detector
configuration. The manifest kept three evidence classes separate: 17 visually
confirmed carriers, 343 Microsoft-provenance files without a visual adjudication,
and 1200 non-overlapping no-signal controls. At the strict 0.38 gate, 15/17
confirmed carriers fired (min 0.249, p50 0.519, p90 0.578, max 0.579), while
0/1200 controls fired (p99 0.200, max 0.293). The provenance cohort produced
78/343 fires, but that is not a recall measurement because provenance identifies
the provider, not the presence of this visible layout. That cohort was later
labeled by an OCR badge census (2026-08-28: 86 badge carriers, 257 badge-less,
badge-less max 0.251 / p99 0.213), which is what enabled the shipped provenance
relaxation 0.7: the relaxed band [0.251, 0.38) holds three faint badges and
zero false fills, re-verified as 3 band detections with 0/257 badge-less fires
on the provenance path.
The detector and removal mask must use compatible geometry. A detector that
fires while producing an empty or misplaced mask is a removal failure even if
@@ -1193,7 +1222,7 @@ were briefly skipped there for exactly that reason.
A mark whose removable footprint differs from what the detector localizes
overrides `_footprint_rect` (which policy) and `_extend_match_box` (how far the
box grows), not the whole `footprint_mask`. Baidu extends right to the corner tag
and LibLibAI extends left to the triangle logo; both inherit every guard around
and LiblibAI extends left to the triangle logo; both inherit every guard around
that arithmetic.
Yuanbao uses the polarity-independent `contrast` front end because its standard
@@ -1395,11 +1424,13 @@ Validation happens before model loading. The library never treats OCR confidence
verification, and geometry-only operators do not need to invent text or script fields.
When enabled, `QwenZImagePipeline` reconstructs the source once through its already
loaded Qwen VAE, runs the ordinary global and face stages, blends 15% of the VAE
reconstruction into that clean result, and calls the shared restoration compositor.
The compositor derives binary source and candidate silhouettes, groups nearby lines,
uses LaMa for the initial and residual-glyph erase passes, paints fresh silhouette
edges, then copies the Qwen-VAE core with a 0.5-pixel feather. The evaluation script
loaded Qwen VAE, runs the ordinary global and face stages, and calls the shared
restoration compositor. The optional fidelity anchor first blends 15% of the VAE
reconstruction into the clean result; it is off by default because the blend returned
detector-visible OpenAI SynthID in the measured poster fixtures. The compositor derives
binary source and candidate silhouettes, groups nearby lines, uses LaMa for the initial
and residual-glyph erase passes, paints fresh silhouette edges, then copies the Qwen-VAE
core with a 0.5-pixel feather. The evaluation script
imports these same mask and compositing helpers so the two implementations cannot
silently drift. Silhouette crops start 12% of line height beyond each horizontal
side, then expand each side independently while a foreground component anchored
@@ -1524,6 +1555,44 @@ sizes the curve's own values verify clean, which is what a resolution-scaled
requirement would predict. There is no measured size at which the shipped curve fails,
so it is left alone.
### Meta Content Seal boundaries for qwen-zimage
Measured 2026-08-26 against the anonymous oracle `meta.ai/identification`
(verdicts read from the settled page text; corpus and full row-level provenance in
`data/contentseal/manifest.csv`). Muse Image carries no C2PA, so
`vendor_for_strength` returns None for it and these images ride the default
resolution-adaptive curve; there is deliberately no `meta` entry in the flat vendor
map, because no provenance signal can establish that cohort automatically and an
unreachable constant would be dead code.
| source (2.56 MP generation) | detected at | clean from |
|---|---|---|
| gen_lighthouse_watercolor | 0.0525 | 0.06 |
| gen_fox_forest | 0.03 | 0.0375 |
| gen_night_city | 0.03 | 0.0375 |
| gen_studio_mug | -- | 0.03 |
| gen_text_poster | -- | 0.015 |
Full spread: worst first-clean boundary (0.0525, 0.06] on lighthouse, easiest
source already clean at 0.015. Following the same derivation as the OpenAI and
Microsoft floors (worst clean boundary plus one full observed cross-source
spread): 0.06 + (0.0525 - 0.015) = 0.0975, rounded up to **0.1**. Shipped as
`QWEN_ZIMAGE_META_STRENGTH` with two routing paths: auto mode routes a file
whose only provenance is the standalone AI IPTC tag onto the cohort
(`vendor_for_strength` checks C2PA issuers first, so Google/OpenAI/Microsoft
evidence always wins, and the tag's other users ship no invisible watermark
this profile targets), and `--vendor meta` / `InvisibleOptions.vendor` names the
cohort explicitly on stripped files, implying the scrub runs (naming the cohort
asserts the watermark is present). sdxl-zimage has no measured Meta rung and an
explicit meta vendor there falls to the conservative unknown 0.25. The default
resolution-adaptive curve (~0.1305 at 2.56 MP) also clears every measured
source, so default behavior needed no change. Oracle verdicts carry a
generation ID and creation timestamp embedded in the watermark payload; both
survived the 512 px resize and JPEG q85 rows, so payload recovery outlives the
detection threshold. Oracle session limits are per-IP, server-side, and
sliding-window: clearing cookies and storage does not reset them, and a burst
exhausts the window minutes after it reopens.
### Static prompt embeddings
Both stages prompt with module constants, and at CFG 1.0 DiffSynth's