{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RMAZBVUTLIM5PN6YXMGDG54CU4","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"effe3dfe82bd06e8a0084c823f288e991b2643b79fe2265f5d56420fd20b7a16","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-15T16:33:59Z","title_canon_sha256":"7ede0030e67c4c10b0e56870fd84ed88f9eb01275aa640da330fc9725974f67f"},"schema_version":"1.0","source":{"id":"2411.10334","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.10334","created_at":"2026-07-05T09:36:03Z"},{"alias_kind":"arxiv_version","alias_value":"2411.10334v1","created_at":"2026-07-05T09:36:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.10334","created_at":"2026-07-05T09:36:03Z"},{"alias_kind":"pith_short_12","alias_value":"RMAZBVUTLIM5","created_at":"2026-07-05T09:36:03Z"},{"alias_kind":"pith_short_16","alias_value":"RMAZBVUTLIM5PN6Y","created_at":"2026-07-05T09:36:03Z"},{"alias_kind":"pith_short_8","alias_value":"RMAZBVUT","created_at":"2026-07-05T09:36:03Z"}],"graph_snapshots":[{"event_id":"sha256:b7d67bf2ea3f1823a022cc234f3fca5a9c44767367f6ef042fa2221ec9789bd2","target":"graph","created_at":"2026-07-05T09:36:03Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2411.10334/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present Y-MAP-Net, a Y-shaped neural network architecture designed for real-time multi-task learning on RGB images. Y-MAP-Net, simultaneously predicts depth, surface normals, human pose, semantic segmentation and generates multi-label captions, all from a single network evaluation. To achieve this, we adopt a multi-teacher, single-student training paradigm, where task-specific foundation models supervise the network's learning, enabling it to distill their capabilities into a lightweight architecture suitable for real-time applications. Y-MAP-Net, exhibits strong generalization, simplicity ","authors_text":"Ammar Qammaz, Antonis A. Argyros, Iason Oikonomidis, Nikolaos Vasilikopoulos","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-15T16:33:59Z","title":"Y-MAP-Net: Real-time depth, normals, segmentation, multi-label captioning and 2D human pose in RGB images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.10334","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:251c4a00ba55887839259b7ba0f7a7740e4c72f93c57c208a94de0f1af7904ca","target":"record","created_at":"2026-07-05T09:36:03Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"effe3dfe82bd06e8a0084c823f288e991b2643b79fe2265f5d56420fd20b7a16","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-15T16:33:59Z","title_canon_sha256":"7ede0030e67c4c10b0e56870fd84ed88f9eb01275aa640da330fc9725974f67f"},"schema_version":"1.0","source":{"id":"2411.10334","kind":"arxiv","version":1}},"canonical_sha256":"8b0190d6935a19d7b7d8bb0c337782a70c675dd6637ee0819a2d770b0a9ab8c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8b0190d6935a19d7b7d8bb0c337782a70c675dd6637ee0819a2d770b0a9ab8c1","first_computed_at":"2026-07-05T09:36:03.595574Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:36:03.595574Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"u5/pJCkIs8xuzBLIT8f7ujRrPx9YMSJh8Jo67ZCECCEjpiCp+MjeoujXVTDjKZdU1KQ3JPZYQ1aiRLkn+5/sAw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:36:03.596101Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.10334","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:251c4a00ba55887839259b7ba0f7a7740e4c72f93c57c208a94de0f1af7904ca","sha256:b7d67bf2ea3f1823a022cc234f3fca5a9c44767367f6ef042fa2221ec9789bd2"],"state_sha256":"fac520eb747299667b207311747b8b9a79e7fc576def2c26d96800cd92d9d3e3"}