pith:IQUOJVRD
Venus-DeFakerOne: Unified Fake Image Detection & Localization
DeFakerOne integrates InternVL2 and SAM2 into one model that detects and localizes image forgeries across many generation types at once.
arxiv:2605.14091 v1 · 2026-05-13 · cs.CV
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\pithnumber{IQUOJVRDDXINXQVA35WDGTNAYW}
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Record completeness
Claims
DeFakerOne achieves state-of-the-art performance, outperforming baselines on 39 forgery detection benchmarks and 9 localization benchmarks.
That integrating InternVL2 and SAM2 with fine-grained supervision sufficiently captures cross-domain artifact transfer and interference without domain-specific adaptations.
DeFakerOne integrates InternVL2 and SAM2 into a single model that achieves state-of-the-art results on 39 detection and 9 localization benchmarks for unified fake image detection and localization.
References
Formal links
Receipt and verification
| First computed | 2026-05-17T23:39:12.210632Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4428e4d6231dd0dbc2a0df6c334da0c58c5ba6a9f05750658916873fb6ccb1ba
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IQUOJVRDDXINXQVA35WDGTNAYW \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 4428e4d6231dd0dbc2a0df6c334da0c58c5ba6a9f05750658916873fb6ccb1ba
Canonical record JSON
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