{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:UJQ5YO75TXUVOW2GKUJRNYG5ET","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":"af060e494288198d57beb7b938fe9b7c8fb9796e2181eb0cc7432649f01cd78e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-09-30T13:10:20Z","title_canon_sha256":"81b2c29a12c8bb899c776d2c76599014752118c63da75a3307db1bf7a5e395d4"},"schema_version":"1.0","source":{"id":"1609.09713","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.09713","created_at":"2026-05-18T01:03:33Z"},{"alias_kind":"arxiv_version","alias_value":"1609.09713v1","created_at":"2026-05-18T01:03:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.09713","created_at":"2026-05-18T01:03:33Z"},{"alias_kind":"pith_short_12","alias_value":"UJQ5YO75TXUV","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_16","alias_value":"UJQ5YO75TXUVOW2G","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_8","alias_value":"UJQ5YO75","created_at":"2026-05-18T12:30:46Z"}],"graph_snapshots":[{"event_id":"sha256:114939fea2651bd19f1e7ebe255eb2180d7e2ef7f8ef5c8c5275f6e10a20b499","target":"graph","created_at":"2026-05-18T01:03:33Z","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"},"paper":{"abstract_excerpt":"Convolutional Neural Networks (CNNs) trained on large scale RGB databases have become the secret sauce in the majority of recent approaches for object categorization from RGB-D data. Thanks to colorization techniques, these methods exploit the filters learned from 2D images to extract meaningful representations in 2.5D. Still, the perceptual signature of these two kind of images is very different, with the first usually strongly characterized by textures, and the second mostly by silhouettes of objects. Ideally, one would like to have two CNNs, one for RGB and one for depth, each trained on a ","authors_text":"Barbara Caputo, Fabio Maria Carlucci, Paolo Russo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-09-30T13:10:20Z","title":"A deep representation for depth images from synthetic data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.09713","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":"sha256:604e08bf294bbb2a08aad199ff400e4ebca30d3f6bd7be6c5fe00eda1deb7b95","target":"record","created_at":"2026-05-18T01:03:33Z","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":"af060e494288198d57beb7b938fe9b7c8fb9796e2181eb0cc7432649f01cd78e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-09-30T13:10:20Z","title_canon_sha256":"81b2c29a12c8bb899c776d2c76599014752118c63da75a3307db1bf7a5e395d4"},"schema_version":"1.0","source":{"id":"1609.09713","kind":"arxiv","version":1}},"canonical_sha256":"a261dc3bfd9de9575b46551316e0dd24dd4567892306ea05670b44ef5a8bc3ac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a261dc3bfd9de9575b46551316e0dd24dd4567892306ea05670b44ef5a8bc3ac","first_computed_at":"2026-05-18T01:03:33.612069Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:03:33.612069Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VQZ/nd3DewF2fqlNEtac33vQI2QxuQgga5Cc6WfbtCzmto288FtTUxsQ6rbYaVVdQ4GDnM3kvj4H43WYbxA5Aw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:03:33.612692Z","signed_message":"canonical_sha256_bytes"},"source_id":"1609.09713","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:604e08bf294bbb2a08aad199ff400e4ebca30d3f6bd7be6c5fe00eda1deb7b95","sha256:114939fea2651bd19f1e7ebe255eb2180d7e2ef7f8ef5c8c5275f6e10a20b499"],"state_sha256":"8168287b9804ba7c3f1014ef2e45354402fc2b16d593f936a9e18e7800e3deda"}