Pith Number
pith:WWRVBQDP
pith:2017:WWRVBQDPCGNC66PGVIQEQBBKD3
not attested
not anchored
not stored
refs pending
Large-scale, Fast and Accurate Shot Boundary Detection through Spatio-temporal Convolutional Neural Networks
arxiv:1705.03281 v2 · 2017-05-09 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{WWRVBQDPCGNC66PGVIQEQBBKD3}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
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claim
4
Citations
5
Replications
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Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Cited by
Receipt and verification
| First computed | 2026-05-18T00:39:22.613580Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b5a350c06f119a2f79e6aa2048042a1ee2cdee5ffa347f27e50e832adebae0da
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/WWRVBQDPCGNC66PGVIQEQBBKD3 \
| 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: b5a350c06f119a2f79e6aa2048042a1ee2cdee5ffa347f27e50e832adebae0da
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "7e60a6a621b762fb159f0e13aa44fa31fdf82a04a62f6f365ce1d5a74dd7f189",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2017-05-09T11:37:25Z",
"title_canon_sha256": "b56d2e30dc371ec67611c611c38177870b2879894049d6b8626a66a5e26948e4"
},
"schema_version": "1.0",
"source": {
"id": "1705.03281",
"kind": "arxiv",
"version": 2
}
}