{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:5DALZMGJKXF42326BUIRLE4MCF","short_pith_number":"pith:5DALZMGJ","canonical_record":{"source":{"id":"2406.10475","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-15T02:40:49Z","cross_cats_sorted":[],"title_canon_sha256":"5f2c6f3c4911c4706c395b4712c9eb2154a5ca1a28043f78b70a6d7a4486a4c0","abstract_canon_sha256":"3d80abfdbce22f552b6f051f5e108174391411bc9949e9108588d388222f0db7"},"schema_version":"1.0"},"canonical_sha256":"e8c0bcb0c955cbcd6f5e0d1115938c11687a3e8273bd92d3a753540f7be57033","source":{"kind":"arxiv","id":"2406.10475","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.10475","created_at":"2026-07-05T08:32:17Z"},{"alias_kind":"arxiv_version","alias_value":"2406.10475v1","created_at":"2026-07-05T08:32:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.10475","created_at":"2026-07-05T08:32:17Z"},{"alias_kind":"pith_short_12","alias_value":"5DALZMGJKXF4","created_at":"2026-07-05T08:32:17Z"},{"alias_kind":"pith_short_16","alias_value":"5DALZMGJKXF42326","created_at":"2026-07-05T08:32:17Z"},{"alias_kind":"pith_short_8","alias_value":"5DALZMGJ","created_at":"2026-07-05T08:32:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:5DALZMGJKXF42326BUIRLE4MCF","target":"record","payload":{"canonical_record":{"source":{"id":"2406.10475","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-15T02:40:49Z","cross_cats_sorted":[],"title_canon_sha256":"5f2c6f3c4911c4706c395b4712c9eb2154a5ca1a28043f78b70a6d7a4486a4c0","abstract_canon_sha256":"3d80abfdbce22f552b6f051f5e108174391411bc9949e9108588d388222f0db7"},"schema_version":"1.0"},"canonical_sha256":"e8c0bcb0c955cbcd6f5e0d1115938c11687a3e8273bd92d3a753540f7be57033","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:32:17.204524Z","signature_b64":"HBsFrmMsUjYswM6irJC72kR9NaeJ8GgJjkLI1GkxL0zuJM+PbSQwGhimu1IoeWnhnUs/KTcWaOCmpPxSk2JWDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e8c0bcb0c955cbcd6f5e0d1115938c11687a3e8273bd92d3a753540f7be57033","last_reissued_at":"2026-07-05T08:32:17.203996Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:32:17.203996Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.10475","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:32:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c/ADFZXYKmEVcoFJnTPFVNCp44eIwrOItyhEMtvSg6ziwn9gU4YsAifvM7M+wgr1zoGu09aexOXafBxf+4NIDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T13:39:10.168694Z"},"content_sha256":"45eac0e125788df7102b973b5205f47996293969e55e84a51541be0bba31b2de","schema_version":"1.0","event_id":"sha256:45eac0e125788df7102b973b5205f47996293969e55e84a51541be0bba31b2de"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:5DALZMGJKXF42326BUIRLE4MCF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Discrete Latent Perspective Learning for Segmentation and Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Deyi Ji, Feng Zhao, Hongtao Lu, Jieping Ye, Lanyun Zhu, Wenwei Jin","submitted_at":"2024-06-15T02:40:49Z","abstract_excerpt":"In this paper, we address the challenge of Perspective-Invariant Learning in machine learning and computer vision, which involves enabling a network to understand images from varying perspectives to achieve consistent semantic interpretation. While standard approaches rely on the labor-intensive collection of multi-view images or limited data augmentation techniques, we propose a novel framework, Discrete Latent Perspective Learning (DLPL), for latent multi-perspective fusion learning using conventional single-view images. DLPL comprises three main modules: Perspective Discrete Decomposition ("},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.10475","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2406.10475/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:32:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nU9ioRxQjPP7NsHq2Fc+wUKJ+/Q1PgidycEVe/pqoRbI8WBfHPXfLekvEFD5cEE+V0NcIWmiCz/wRF5lWVVaBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T13:39:10.169237Z"},"content_sha256":"37cef324c21c5053fe01b14c74be47469cc14dc824991dfc404f27616ef43738","schema_version":"1.0","event_id":"sha256:37cef324c21c5053fe01b14c74be47469cc14dc824991dfc404f27616ef43738"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5DALZMGJKXF42326BUIRLE4MCF/bundle.json","state_url":"https://pith.science/pith/5DALZMGJKXF42326BUIRLE4MCF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5DALZMGJKXF42326BUIRLE4MCF/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-11T13:39:10Z","links":{"resolver":"https://pith.science/pith/5DALZMGJKXF42326BUIRLE4MCF","bundle":"https://pith.science/pith/5DALZMGJKXF42326BUIRLE4MCF/bundle.json","state":"https://pith.science/pith/5DALZMGJKXF42326BUIRLE4MCF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5DALZMGJKXF42326BUIRLE4MCF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5DALZMGJKXF42326BUIRLE4MCF","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":"3d80abfdbce22f552b6f051f5e108174391411bc9949e9108588d388222f0db7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-15T02:40:49Z","title_canon_sha256":"5f2c6f3c4911c4706c395b4712c9eb2154a5ca1a28043f78b70a6d7a4486a4c0"},"schema_version":"1.0","source":{"id":"2406.10475","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.10475","created_at":"2026-07-05T08:32:17Z"},{"alias_kind":"arxiv_version","alias_value":"2406.10475v1","created_at":"2026-07-05T08:32:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.10475","created_at":"2026-07-05T08:32:17Z"},{"alias_kind":"pith_short_12","alias_value":"5DALZMGJKXF4","created_at":"2026-07-05T08:32:17Z"},{"alias_kind":"pith_short_16","alias_value":"5DALZMGJKXF42326","created_at":"2026-07-05T08:32:17Z"},{"alias_kind":"pith_short_8","alias_value":"5DALZMGJ","created_at":"2026-07-05T08:32:17Z"}],"graph_snapshots":[{"event_id":"sha256:37cef324c21c5053fe01b14c74be47469cc14dc824991dfc404f27616ef43738","target":"graph","created_at":"2026-07-05T08:32:17Z","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/2406.10475/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we address the challenge of Perspective-Invariant Learning in machine learning and computer vision, which involves enabling a network to understand images from varying perspectives to achieve consistent semantic interpretation. While standard approaches rely on the labor-intensive collection of multi-view images or limited data augmentation techniques, we propose a novel framework, Discrete Latent Perspective Learning (DLPL), for latent multi-perspective fusion learning using conventional single-view images. DLPL comprises three main modules: Perspective Discrete Decomposition (","authors_text":"Deyi Ji, Feng Zhao, Hongtao Lu, Jieping Ye, Lanyun Zhu, Wenwei Jin","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-15T02:40:49Z","title":"Discrete Latent Perspective Learning for Segmentation and Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.10475","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":"sha256:45eac0e125788df7102b973b5205f47996293969e55e84a51541be0bba31b2de","target":"record","created_at":"2026-07-05T08:32:17Z","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":"3d80abfdbce22f552b6f051f5e108174391411bc9949e9108588d388222f0db7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-15T02:40:49Z","title_canon_sha256":"5f2c6f3c4911c4706c395b4712c9eb2154a5ca1a28043f78b70a6d7a4486a4c0"},"schema_version":"1.0","source":{"id":"2406.10475","kind":"arxiv","version":1}},"canonical_sha256":"e8c0bcb0c955cbcd6f5e0d1115938c11687a3e8273bd92d3a753540f7be57033","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e8c0bcb0c955cbcd6f5e0d1115938c11687a3e8273bd92d3a753540f7be57033","first_computed_at":"2026-07-05T08:32:17.203996Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:32:17.203996Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HBsFrmMsUjYswM6irJC72kR9NaeJ8GgJjkLI1GkxL0zuJM+PbSQwGhimu1IoeWnhnUs/KTcWaOCmpPxSk2JWDg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:32:17.204524Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.10475","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:45eac0e125788df7102b973b5205f47996293969e55e84a51541be0bba31b2de","sha256:37cef324c21c5053fe01b14c74be47469cc14dc824991dfc404f27616ef43738"],"state_sha256":"5f07d289e6a4cfc7ce01ea2fbe347f9da72ec29202b3e60cfe28eb0d8587740e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/eZm9uSTvIdOFxEi0pX3G30dVGAtUkLvcNe2jclGI6+7woAyqQtjMovqm2C5CJcbz+1QxApogHX6SJXboX65CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T13:39:10.176568Z","bundle_sha256":"8f025ee17f0357adda4ab59cabc806a7ea735d05345ccbd16c5e4a4af47057f4"}}