pith:4PH2U7EJ
ScriptHOI: Learning Scripted State Transitions for Open-Vocabulary Human-Object Interaction Detection
Decomposing interaction phrases into state slots verifies multiple visual cues and improves rare and unseen human-object interaction detection.
arxiv:2605.05057 v3 · 2026-05-06 · cs.CV
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Record completeness
Claims
Experiments on HICO-DET, V-COCO, and open-vocabulary HOI splits show that ScriptHOI improves rare and unseen interaction recognition while substantially reducing affordance-conflict false positives.
That the visual state tokenizer can reliably parse human-object pairs into accurate state tokens for the six slots and that script coverage and conflict estimates provide valid calibration without introducing new biases or missing critical visual cues.
ScriptHOI improves rare and unseen HOI recognition by decomposing phrases into state slots, using visual tokenization and slot-wise matching for script coverage and conflict to calibrate predictions and constrain training on incomplete labels.
Receipt and verification
| First computed | 2026-05-27T01:04:58.799764Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
e3cfaa7c89ece5db00cb06792c8efc5180aded54535774509e9f54a89bf8998a
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/4PH2U7EJ5TS5WAGLAZ4SZDX4KG \
| 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: e3cfaa7c89ece5db00cb06792c8efc5180aded54535774509e9f54a89bf8998a
Canonical record JSON
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