{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:KZTUVMRXGNF75NAXKWSXNLO52H","short_pith_number":"pith:KZTUVMRX","canonical_record":{"source":{"id":"2401.11414","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-01-21T06:47:33Z","cross_cats_sorted":["cs.AI","cs.RO"],"title_canon_sha256":"d105c2346594fce25c035f6e46b5259d434aa0e8e5c4c57a2efce290bc3c97bc","abstract_canon_sha256":"7c53f1836dee59b1f06001b617a708aba22f2e715ada4d2a87b1a6311ffe07f6"},"schema_version":"1.0"},"canonical_sha256":"56674ab237334bfeb41755a576adddd1eaf045ee80cbc37ab6128943b314520e","source":{"kind":"arxiv","id":"2401.11414","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.11414","created_at":"2026-07-05T07:38:34Z"},{"alias_kind":"arxiv_version","alias_value":"2401.11414v2","created_at":"2026-07-05T07:38:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.11414","created_at":"2026-07-05T07:38:34Z"},{"alias_kind":"pith_short_12","alias_value":"KZTUVMRXGNF7","created_at":"2026-07-05T07:38:34Z"},{"alias_kind":"pith_short_16","alias_value":"KZTUVMRXGNF75NAX","created_at":"2026-07-05T07:38:34Z"},{"alias_kind":"pith_short_8","alias_value":"KZTUVMRX","created_at":"2026-07-05T07:38:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:KZTUVMRXGNF75NAXKWSXNLO52H","target":"record","payload":{"canonical_record":{"source":{"id":"2401.11414","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-01-21T06:47:33Z","cross_cats_sorted":["cs.AI","cs.RO"],"title_canon_sha256":"d105c2346594fce25c035f6e46b5259d434aa0e8e5c4c57a2efce290bc3c97bc","abstract_canon_sha256":"7c53f1836dee59b1f06001b617a708aba22f2e715ada4d2a87b1a6311ffe07f6"},"schema_version":"1.0"},"canonical_sha256":"56674ab237334bfeb41755a576adddd1eaf045ee80cbc37ab6128943b314520e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:38:34.600141Z","signature_b64":"boYWGaLGIKX0d0f9ou/kRK9VfKK9QURvuU3EI8pW6bbxyO73PO1a9lP6JVPePcfYEn9YnX7OYalD/29T3EXBCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"56674ab237334bfeb41755a576adddd1eaf045ee80cbc37ab6128943b314520e","last_reissued_at":"2026-07-05T07:38:34.599693Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:38:34.599693Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.11414","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":"2026-07-05T07:38:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F0tOVJqTxYIjzXd1iU0NGwIuht5ZsUZSJaHhP/0i1i/wU9D1XcppajJLIIdwUottVaifXESb9DbLHbzs3Q0CDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T20:12:11.696909Z"},"content_sha256":"6bfcb2ef4464ed53df2e7741e7801bd8248f28cc58c6d22659944b262e02db1c","schema_version":"1.0","event_id":"sha256:6bfcb2ef4464ed53df2e7741e7801bd8248f28cc58c6d22659944b262e02db1c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:KZTUVMRXGNF75NAXKWSXNLO52H","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"S$^3$M-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Driving","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.RO"],"primary_cat":"cs.CV","authors_text":"Chuang-Wei Liu, Fisher Yu, Qijun Chen, Rui Fan, Yi Feng, Zhiyuan Wu","submitted_at":"2024-01-21T06:47:33Z","abstract_excerpt":"Semantic segmentation and stereo matching are two essential components of 3D environmental perception systems for autonomous driving. Nevertheless, conventional approaches often address these two problems independently, employing separate models for each task. This approach poses practical limitations in real-world scenarios, particularly when computational resources are scarce or real-time performance is imperative. Hence, in this article, we introduce S$^3$M-Net, a novel joint learning framework developed to perform semantic segmentation and stereo matching simultaneously. Specifically, S$^3"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.11414","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/2401.11414/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":"2026-07-05T07:38:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YMB0/v59LxX8S1MIrTPA7JcRxnQRyh7ioXrkSdKJ65TzWJJg+se661iSLrlr7T7rNJohkX5oXrflvNNUcWTsBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T20:12:11.697436Z"},"content_sha256":"28c3c525957e3b51f0b9dbde68641e177c8502410a6dde9e987c3d6319344964","schema_version":"1.0","event_id":"sha256:28c3c525957e3b51f0b9dbde68641e177c8502410a6dde9e987c3d6319344964"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KZTUVMRXGNF75NAXKWSXNLO52H/bundle.json","state_url":"https://pith.science/pith/KZTUVMRXGNF75NAXKWSXNLO52H/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KZTUVMRXGNF75NAXKWSXNLO52H/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":"2026-08-13T20:12:11Z","links":{"resolver":"https://pith.science/pith/KZTUVMRXGNF75NAXKWSXNLO52H","bundle":"https://pith.science/pith/KZTUVMRXGNF75NAXKWSXNLO52H/bundle.json","state":"https://pith.science/pith/KZTUVMRXGNF75NAXKWSXNLO52H/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KZTUVMRXGNF75NAXKWSXNLO52H/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KZTUVMRXGNF75NAXKWSXNLO52H","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":"7c53f1836dee59b1f06001b617a708aba22f2e715ada4d2a87b1a6311ffe07f6","cross_cats_sorted":["cs.AI","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-01-21T06:47:33Z","title_canon_sha256":"d105c2346594fce25c035f6e46b5259d434aa0e8e5c4c57a2efce290bc3c97bc"},"schema_version":"1.0","source":{"id":"2401.11414","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.11414","created_at":"2026-07-05T07:38:34Z"},{"alias_kind":"arxiv_version","alias_value":"2401.11414v2","created_at":"2026-07-05T07:38:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.11414","created_at":"2026-07-05T07:38:34Z"},{"alias_kind":"pith_short_12","alias_value":"KZTUVMRXGNF7","created_at":"2026-07-05T07:38:34Z"},{"alias_kind":"pith_short_16","alias_value":"KZTUVMRXGNF75NAX","created_at":"2026-07-05T07:38:34Z"},{"alias_kind":"pith_short_8","alias_value":"KZTUVMRX","created_at":"2026-07-05T07:38:34Z"}],"graph_snapshots":[{"event_id":"sha256:28c3c525957e3b51f0b9dbde68641e177c8502410a6dde9e987c3d6319344964","target":"graph","created_at":"2026-07-05T07:38:34Z","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/2401.11414/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semantic segmentation and stereo matching are two essential components of 3D environmental perception systems for autonomous driving. Nevertheless, conventional approaches often address these two problems independently, employing separate models for each task. This approach poses practical limitations in real-world scenarios, particularly when computational resources are scarce or real-time performance is imperative. Hence, in this article, we introduce S$^3$M-Net, a novel joint learning framework developed to perform semantic segmentation and stereo matching simultaneously. Specifically, S$^3","authors_text":"Chuang-Wei Liu, Fisher Yu, Qijun Chen, Rui Fan, Yi Feng, Zhiyuan Wu","cross_cats":["cs.AI","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-01-21T06:47:33Z","title":"S$^3$M-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Driving"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.11414","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":"sha256:6bfcb2ef4464ed53df2e7741e7801bd8248f28cc58c6d22659944b262e02db1c","target":"record","created_at":"2026-07-05T07:38:34Z","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":"7c53f1836dee59b1f06001b617a708aba22f2e715ada4d2a87b1a6311ffe07f6","cross_cats_sorted":["cs.AI","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-01-21T06:47:33Z","title_canon_sha256":"d105c2346594fce25c035f6e46b5259d434aa0e8e5c4c57a2efce290bc3c97bc"},"schema_version":"1.0","source":{"id":"2401.11414","kind":"arxiv","version":2}},"canonical_sha256":"56674ab237334bfeb41755a576adddd1eaf045ee80cbc37ab6128943b314520e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"56674ab237334bfeb41755a576adddd1eaf045ee80cbc37ab6128943b314520e","first_computed_at":"2026-07-05T07:38:34.599693Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:38:34.599693Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"boYWGaLGIKX0d0f9ou/kRK9VfKK9QURvuU3EI8pW6bbxyO73PO1a9lP6JVPePcfYEn9YnX7OYalD/29T3EXBCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:38:34.600141Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.11414","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6bfcb2ef4464ed53df2e7741e7801bd8248f28cc58c6d22659944b262e02db1c","sha256:28c3c525957e3b51f0b9dbde68641e177c8502410a6dde9e987c3d6319344964"],"state_sha256":"81055da806613d4c10f56fab17217f3abd6de00ee5b379d65f47e5c4ac33bad3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r4Ipa3ifkUlHS898IKsq0pg6ZN9rVfwKG7rDD2PXk9koFXI3O9JAT32Fw2JX20Ry5tppxLsUOtM/4juERMLQDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T20:12:11.703772Z","bundle_sha256":"85de6b5db7c82cb4c9b5d8beefd0bb1ab377180f3af88731891988fc25164b5a"}}