{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:NNDMEXDPNVX32GVAHHIVSJ5KDI","short_pith_number":"pith:NNDMEXDP","canonical_record":{"source":{"id":"2409.07995","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-12T12:39:34Z","cross_cats_sorted":[],"title_canon_sha256":"6254cf735e7d5e27e7cef422d898e95d9b72449867fdef63aa8620b26c42950b","abstract_canon_sha256":"424cca2fb979b64d47e18d563044d52df1eecd0698ffec31925ba7f8ad31197b"},"schema_version":"1.0"},"canonical_sha256":"6b46c25c6f6d6fbd1aa039d15927aa1a11582fe0f50642ecf01b098108aa4cf1","source":{"kind":"arxiv","id":"2409.07995","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.07995","created_at":"2026-07-05T11:29:49Z"},{"alias_kind":"arxiv_version","alias_value":"2409.07995v2","created_at":"2026-07-05T11:29:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.07995","created_at":"2026-07-05T11:29:49Z"},{"alias_kind":"pith_short_12","alias_value":"NNDMEXDPNVX3","created_at":"2026-07-05T11:29:49Z"},{"alias_kind":"pith_short_16","alias_value":"NNDMEXDPNVX32GVA","created_at":"2026-07-05T11:29:49Z"},{"alias_kind":"pith_short_8","alias_value":"NNDMEXDP","created_at":"2026-07-05T11:29:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:NNDMEXDPNVX32GVAHHIVSJ5KDI","target":"record","payload":{"canonical_record":{"source":{"id":"2409.07995","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-12T12:39:34Z","cross_cats_sorted":[],"title_canon_sha256":"6254cf735e7d5e27e7cef422d898e95d9b72449867fdef63aa8620b26c42950b","abstract_canon_sha256":"424cca2fb979b64d47e18d563044d52df1eecd0698ffec31925ba7f8ad31197b"},"schema_version":"1.0"},"canonical_sha256":"6b46c25c6f6d6fbd1aa039d15927aa1a11582fe0f50642ecf01b098108aa4cf1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:29:49.683607Z","signature_b64":"xtpy2TqBG6Pe/XM417+KUfGBxGDMZEO+bkPdCc7A1rxVYYIse/Gm+6muhzSmO2+LAo4XFQFiRdWODbI7Tg/aBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6b46c25c6f6d6fbd1aa039d15927aa1a11582fe0f50642ecf01b098108aa4cf1","last_reissued_at":"2026-07-05T11:29:49.682897Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:29:49.682897Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.07995","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:29:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xoBKA89z445XPPckcYPEMA/cU0ug4GzCOya+TNgq0CUtJTZ6I9Xfn8EVQ0yzeLwy7UF3kq4ndLLcRHdRFaRQAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T11:34:01.343533Z"},"content_sha256":"01e517c8a423796b1c835593e1aae3b8c064b17abc2cdf64b14f1d64036cbc3c","schema_version":"1.0","event_id":"sha256:01e517c8a423796b1c835593e1aae3b8c064b17abc2cdf64b14f1d64036cbc3c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:NNDMEXDPNVX32GVAHHIVSJ5KDI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Depth Matters: Exploring Deep Interactions of RGB-D for Semantic Segmentation in Traffic Scenes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Changshe Zhang, Guorong Cai, Jinhe Su, Siyu Chen, Ting Han, Weiquan Liu, Zongyue Wang","submitted_at":"2024-09-12T12:39:34Z","abstract_excerpt":"RGB-D has gradually become a crucial data source for understanding complex scenes in assisted driving. However, existing studies have paid insufficient attention to the intrinsic spatial properties of depth maps. This oversight significantly impacts the attention representation, leading to prediction errors caused by attention shift issues. To this end, we propose a novel learnable Depth interaction Pyramid Transformer (DiPFormer) to explore the effectiveness of depth. Firstly, we introduce Depth Spatial-Aware Optimization (Depth SAO) as offset to represent real-world spatial relationships. Se"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.07995","kind":"arxiv","version":2},"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/2409.07995/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":"2026-07-05T11:29:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"glCLK+O5lGxnedSwu9dHNpKfVa+MZSTWPVLs8AewT+0PfbnWm6ktGVhAxh9sFodZY/zw755O9UGQMmUaUY+wCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T11:34:01.343904Z"},"content_sha256":"f06b58dc216f56e1062bd987502f1e87152f804aa414aa4d426a959e6d158520","schema_version":"1.0","event_id":"sha256:f06b58dc216f56e1062bd987502f1e87152f804aa414aa4d426a959e6d158520"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NNDMEXDPNVX32GVAHHIVSJ5KDI/bundle.json","state_url":"https://pith.science/pith/NNDMEXDPNVX32GVAHHIVSJ5KDI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NNDMEXDPNVX32GVAHHIVSJ5KDI/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":"2026-07-11T11:34:01Z","links":{"resolver":"https://pith.science/pith/NNDMEXDPNVX32GVAHHIVSJ5KDI","bundle":"https://pith.science/pith/NNDMEXDPNVX32GVAHHIVSJ5KDI/bundle.json","state":"https://pith.science/pith/NNDMEXDPNVX32GVAHHIVSJ5KDI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NNDMEXDPNVX32GVAHHIVSJ5KDI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NNDMEXDPNVX32GVAHHIVSJ5KDI","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":"424cca2fb979b64d47e18d563044d52df1eecd0698ffec31925ba7f8ad31197b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-12T12:39:34Z","title_canon_sha256":"6254cf735e7d5e27e7cef422d898e95d9b72449867fdef63aa8620b26c42950b"},"schema_version":"1.0","source":{"id":"2409.07995","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.07995","created_at":"2026-07-05T11:29:49Z"},{"alias_kind":"arxiv_version","alias_value":"2409.07995v2","created_at":"2026-07-05T11:29:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.07995","created_at":"2026-07-05T11:29:49Z"},{"alias_kind":"pith_short_12","alias_value":"NNDMEXDPNVX3","created_at":"2026-07-05T11:29:49Z"},{"alias_kind":"pith_short_16","alias_value":"NNDMEXDPNVX32GVA","created_at":"2026-07-05T11:29:49Z"},{"alias_kind":"pith_short_8","alias_value":"NNDMEXDP","created_at":"2026-07-05T11:29:49Z"}],"graph_snapshots":[{"event_id":"sha256:f06b58dc216f56e1062bd987502f1e87152f804aa414aa4d426a959e6d158520","target":"graph","created_at":"2026-07-05T11:29:49Z","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/2409.07995/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"RGB-D has gradually become a crucial data source for understanding complex scenes in assisted driving. However, existing studies have paid insufficient attention to the intrinsic spatial properties of depth maps. This oversight significantly impacts the attention representation, leading to prediction errors caused by attention shift issues. To this end, we propose a novel learnable Depth interaction Pyramid Transformer (DiPFormer) to explore the effectiveness of depth. Firstly, we introduce Depth Spatial-Aware Optimization (Depth SAO) as offset to represent real-world spatial relationships. Se","authors_text":"Changshe Zhang, Guorong Cai, Jinhe Su, Siyu Chen, Ting Han, Weiquan Liu, Zongyue Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-12T12:39:34Z","title":"Depth Matters: Exploring Deep Interactions of RGB-D for Semantic Segmentation in Traffic Scenes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.07995","kind":"arxiv","version":2},"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":"sha256:01e517c8a423796b1c835593e1aae3b8c064b17abc2cdf64b14f1d64036cbc3c","target":"record","created_at":"2026-07-05T11:29:49Z","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":"424cca2fb979b64d47e18d563044d52df1eecd0698ffec31925ba7f8ad31197b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-12T12:39:34Z","title_canon_sha256":"6254cf735e7d5e27e7cef422d898e95d9b72449867fdef63aa8620b26c42950b"},"schema_version":"1.0","source":{"id":"2409.07995","kind":"arxiv","version":2}},"canonical_sha256":"6b46c25c6f6d6fbd1aa039d15927aa1a11582fe0f50642ecf01b098108aa4cf1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6b46c25c6f6d6fbd1aa039d15927aa1a11582fe0f50642ecf01b098108aa4cf1","first_computed_at":"2026-07-05T11:29:49.682897Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:29:49.682897Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xtpy2TqBG6Pe/XM417+KUfGBxGDMZEO+bkPdCc7A1rxVYYIse/Gm+6muhzSmO2+LAo4XFQFiRdWODbI7Tg/aBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:29:49.683607Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.07995","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:01e517c8a423796b1c835593e1aae3b8c064b17abc2cdf64b14f1d64036cbc3c","sha256:f06b58dc216f56e1062bd987502f1e87152f804aa414aa4d426a959e6d158520"],"state_sha256":"150ac5dc9d7c3098c92a9e06ef7a3b9407e5af2ea5f49d65bde4b63387d28de4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4iJ8gOkaiW/2N+nMTz/QLNmkGEb5JHY07RTdxLo88nCzZ0rSbhMwpPlMcMGRpxM6fiC7qJXrcngdpGsZ0yTkCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T11:34:01.346352Z","bundle_sha256":"18cf7507c9dfe6db3b402669b610231da523d200e0f663385140a741b3804d33"}}