{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:DLIUU57KQV22SOIGQ6NOE324M4","short_pith_number":"pith:DLIUU57K","canonical_record":{"source":{"id":"2002.10570","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-24T22:17:25Z","cross_cats_sorted":["cs.RO","eess.IV"],"title_canon_sha256":"8baf71c64f7583a0a51ad977e626b43c5a352347e6f89c4bb43004973f206b00","abstract_canon_sha256":"99ee628058850c80afb62b8bd344767030a2559b34c3f2458f5b308a90c832af"},"schema_version":"1.0"},"canonical_sha256":"1ad14a77ea8575a93906879ae26f5c671ddb56191d5bed0b95a2d19e09530ffe","source":{"kind":"arxiv","id":"2002.10570","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.10570","created_at":"2026-07-05T01:13:58Z"},{"alias_kind":"arxiv_version","alias_value":"2002.10570v2","created_at":"2026-07-05T01:13:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.10570","created_at":"2026-07-05T01:13:58Z"},{"alias_kind":"pith_short_12","alias_value":"DLIUU57KQV22","created_at":"2026-07-05T01:13:58Z"},{"alias_kind":"pith_short_16","alias_value":"DLIUU57KQV22SOIG","created_at":"2026-07-05T01:13:58Z"},{"alias_kind":"pith_short_8","alias_value":"DLIUU57K","created_at":"2026-07-05T01:13:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:DLIUU57KQV22SOIGQ6NOE324M4","target":"record","payload":{"canonical_record":{"source":{"id":"2002.10570","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-24T22:17:25Z","cross_cats_sorted":["cs.RO","eess.IV"],"title_canon_sha256":"8baf71c64f7583a0a51ad977e626b43c5a352347e6f89c4bb43004973f206b00","abstract_canon_sha256":"99ee628058850c80afb62b8bd344767030a2559b34c3f2458f5b308a90c832af"},"schema_version":"1.0"},"canonical_sha256":"1ad14a77ea8575a93906879ae26f5c671ddb56191d5bed0b95a2d19e09530ffe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:13:58.432257Z","signature_b64":"oSCxx3mffBQUuLDycphD6fZyTnJr68uHWnIow0BxBC02eUOG3bcBTDmsh2rQmT3cPwrM29ZfopbIDMaI9JUhBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1ad14a77ea8575a93906879ae26f5c671ddb56191d5bed0b95a2d19e09530ffe","last_reissued_at":"2026-07-05T01:13:58.431852Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:13:58.431852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.10570","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":"2026-07-05T01:13:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6k/WRFgAPwQOX9eVfUHmzWKu/cgN+mYOSGZErXPBWbYn6WhOlnWRYEj3NmTK6v6ST0CrV+ZkCH48HgJXUZH7Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T19:54:45.789762Z"},"content_sha256":"3fe6270fcf305ba86bc127aef13291c785e23d1018658863093cc9e38d3f690d","schema_version":"1.0","event_id":"sha256:3fe6270fcf305ba86bc127aef13291c785e23d1018658863093cc9e38d3f690d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:DLIUU57KQV22SOIGQ6NOE324M4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Real-time Fusion Network for RGB-D Semantic Segmentation Incorporating Unexpected Obstacle Detection for Road-driving Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO","eess.IV"],"primary_cat":"cs.CV","authors_text":"Kailun Yang, Kaiwei Wang, Lei Sun, Weijian Hu, Xinxin Hu","submitted_at":"2020-02-24T22:17:25Z","abstract_excerpt":"Semantic segmentation has made striking progress due to the success of deep convolutional neural networks. Considering the demands of autonomous driving, real-time semantic segmentation has become a research hotspot these years. However, few real-time RGB-D fusion semantic segmentation studies are carried out despite readily accessible depth information nowadays. In this paper, we propose a real-time fusion semantic segmentation network termed RFNet that effectively exploits complementary cross-modal information. Building on an efficient network architecture, RFNet is capable of running swiftl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.10570","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/2002.10570/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":"2026-07-05T01:13:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f5gU0bgwhBBakKZZKOm2raYBcNg0GhwB1hpBy6RS1t5mfSQYA5BPbso0+/GWL3+mSlbPf9F5VTAtlEb1UUVZDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T19:54:45.790732Z"},"content_sha256":"9492b61538ef83a274ae3fce9d723f626d31cc5c2c21d35ede8928040a560bac","schema_version":"1.0","event_id":"sha256:9492b61538ef83a274ae3fce9d723f626d31cc5c2c21d35ede8928040a560bac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DLIUU57KQV22SOIGQ6NOE324M4/bundle.json","state_url":"https://pith.science/pith/DLIUU57KQV22SOIGQ6NOE324M4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DLIUU57KQV22SOIGQ6NOE324M4/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":"2026-08-23T19:54:45Z","links":{"resolver":"https://pith.science/pith/DLIUU57KQV22SOIGQ6NOE324M4","bundle":"https://pith.science/pith/DLIUU57KQV22SOIGQ6NOE324M4/bundle.json","state":"https://pith.science/pith/DLIUU57KQV22SOIGQ6NOE324M4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DLIUU57KQV22SOIGQ6NOE324M4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:DLIUU57KQV22SOIGQ6NOE324M4","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":"99ee628058850c80afb62b8bd344767030a2559b34c3f2458f5b308a90c832af","cross_cats_sorted":["cs.RO","eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-24T22:17:25Z","title_canon_sha256":"8baf71c64f7583a0a51ad977e626b43c5a352347e6f89c4bb43004973f206b00"},"schema_version":"1.0","source":{"id":"2002.10570","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.10570","created_at":"2026-07-05T01:13:58Z"},{"alias_kind":"arxiv_version","alias_value":"2002.10570v2","created_at":"2026-07-05T01:13:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.10570","created_at":"2026-07-05T01:13:58Z"},{"alias_kind":"pith_short_12","alias_value":"DLIUU57KQV22","created_at":"2026-07-05T01:13:58Z"},{"alias_kind":"pith_short_16","alias_value":"DLIUU57KQV22SOIG","created_at":"2026-07-05T01:13:58Z"},{"alias_kind":"pith_short_8","alias_value":"DLIUU57K","created_at":"2026-07-05T01:13:58Z"}],"graph_snapshots":[{"event_id":"sha256:9492b61538ef83a274ae3fce9d723f626d31cc5c2c21d35ede8928040a560bac","target":"graph","created_at":"2026-07-05T01:13:58Z","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/2002.10570/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semantic segmentation has made striking progress due to the success of deep convolutional neural networks. Considering the demands of autonomous driving, real-time semantic segmentation has become a research hotspot these years. However, few real-time RGB-D fusion semantic segmentation studies are carried out despite readily accessible depth information nowadays. In this paper, we propose a real-time fusion semantic segmentation network termed RFNet that effectively exploits complementary cross-modal information. Building on an efficient network architecture, RFNet is capable of running swiftl","authors_text":"Kailun Yang, Kaiwei Wang, Lei Sun, Weijian Hu, Xinxin Hu","cross_cats":["cs.RO","eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-24T22:17:25Z","title":"Real-time Fusion Network for RGB-D Semantic Segmentation Incorporating Unexpected Obstacle Detection for Road-driving Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.10570","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":"sha256:3fe6270fcf305ba86bc127aef13291c785e23d1018658863093cc9e38d3f690d","target":"record","created_at":"2026-07-05T01:13:58Z","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":"99ee628058850c80afb62b8bd344767030a2559b34c3f2458f5b308a90c832af","cross_cats_sorted":["cs.RO","eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-24T22:17:25Z","title_canon_sha256":"8baf71c64f7583a0a51ad977e626b43c5a352347e6f89c4bb43004973f206b00"},"schema_version":"1.0","source":{"id":"2002.10570","kind":"arxiv","version":2}},"canonical_sha256":"1ad14a77ea8575a93906879ae26f5c671ddb56191d5bed0b95a2d19e09530ffe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1ad14a77ea8575a93906879ae26f5c671ddb56191d5bed0b95a2d19e09530ffe","first_computed_at":"2026-07-05T01:13:58.431852Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:13:58.431852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oSCxx3mffBQUuLDycphD6fZyTnJr68uHWnIow0BxBC02eUOG3bcBTDmsh2rQmT3cPwrM29ZfopbIDMaI9JUhBw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:13:58.432257Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.10570","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3fe6270fcf305ba86bc127aef13291c785e23d1018658863093cc9e38d3f690d","sha256:9492b61538ef83a274ae3fce9d723f626d31cc5c2c21d35ede8928040a560bac"],"state_sha256":"93951f5eb4379ff4e2b6d345a39ee01dd25a10e13cab6cf3110d1897a7bdbaed"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sn5ahiC2Ca4AaY6MAnJYyIQAICoI+OeQyxQzqllE3aPIpCuZFT8rnMRs/SacsgheE1WDDcq8EV0IZDif8l25CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T19:54:45.797215Z","bundle_sha256":"0fd3cbda2be6de872311b02065ceb2ed135cf0d8c01155a51465c027a32c4cdd"}}