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ContactCut: A Partition-Aware Contact Selection Framework for False-Merge Correction in Connectomics — arXiv:2611.01457

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.01457
License (as archived): CC0-1.0
Archived: 2026-11-03T18:53:25.107Z
SHA-256 of the archived text: bafb010a73e8e7807fa1f2a15a2b6a38c63c84e83ea6c481c659d7bef2be48c3
Stable URL of this page: https://metraipolis.com/documento/dc_aa33cc8042e2

How to cite

ContactCut: A Partition-Aware Contact Selection Framework for False-Merge Correction in Connectomics — arXiv:2611.01457 — arXiv (en), https://arxiv.org/abs/2611.01457 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_aa33cc8042e2 (Metraipolis archive dc_aa33cc8042e2, sha256 bafb010a73e8e7807fa1f2a15a2b6a38c63c84e83ea6c481c659d7bef2be48c3)

BibTeX

@misc{dcaa33cc8042e2,
  title = {ContactCut: A Partition-Aware Contact Selection Framework for False-Merge Correction in Connectomics — arXiv:2611.01457},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.01457},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_aa33cc8042e2; sha256 bafb010a73e8e7807fa1f2a15a2b6a38c63c84e83ea6c481c659d7bef2be48c3},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.01457. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Localized false-merge correction in connectomics requires converting an identified error into an executable native 3D partition. Still, neither intermediate correction predictions nor seeded graph solvers alone determine which native source-sink constraints should define that partition. We formulate this problem as a 3D-native partition-aware contact selection problem: selecting candidate contacts based on the complete partitions they induce. Our solution comprises two components: ContactCut (CC)-Auto, which uses learned single-contact selection, and ContactCut (CC)-Search, which enables bounded paired-contact search, generates compact alternatives, and applies learned panel ranking. On historical two-way false-merge corrections from MICrONS and FlyWire, CC-Auto improves failure-aware 3D partition (FA-3D Part.) mIoU by 5.9 and 3.4 points over the strongest graph-based controls and by 12.5 and 10.0 points over the best learned baselines. A MICrONS-trained ranker transfers to FlyWire with negligible degradation. CC-Search expands oracle reachability and prioritizes near-oracle alternatives. The code is available at this https URL .

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv cs.CV, nuovi lavori del giorno).
Categorie arXiv: Computer Vision and Pattern Recognition (cs.CV).
Pagina del lavoro: https://arxiv.org/abs/2611.01457 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-03T18:16:52.926Z dalla pagina https://arxiv.org/list/cs.CV/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).