Pith Number
pith:LRTVTARP
pith:2020:LRTVTARPHTXBOFB7SDTCGLO76F
not attested
not anchored
not stored
refs pending
3D Object Recognition By Corresponding and Quantizing Neural 3D Scene Representations
arxiv:2010.16279 v1 · 2020-10-30 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{LRTVTARPHTXBOFB7SDTCGLO76F}
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.
Receipt and verification
| First computed | 2026-07-05T01:47:51.479686Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
5c6759822f3cee17143f90e6232ddff14536350a6792ae9bd6be81a7d7f12d2c
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/LRTVTARPHTXBOFB7SDTCGLO76F \
| 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: 5c6759822f3cee17143f90e6232ddff14536350a6792ae9bd6be81a7d7f12d2c
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "109cbdbf5b05bf881c14bc03a5a6b23ab7eeb5357ed80f06ba099b0fabafc911",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2020-10-30T13:56:09Z",
"title_canon_sha256": "4135f6f1440e18dfc616cac84ee682c588c405aee40f872d5a8504ef0f724a82"
},
"schema_version": "1.0",
"source": {
"id": "2010.16279",
"kind": "arxiv",
"version": 1
}
}