{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:OZ2CI3UMWSPJ4MATQQYHMY4ZOK","short_pith_number":"pith:OZ2CI3UM","canonical_record":{"source":{"id":"2112.00582","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-12-01T15:53:58Z","cross_cats_sorted":[],"title_canon_sha256":"f098c883a23ccface85441301705e596f0a7869c6963efe7763d1ab2e1443c66","abstract_canon_sha256":"1e64f165a20473b586113f962f033de91ce5336cf6573927e458fcf4f926e170"},"schema_version":"1.0"},"canonical_sha256":"7674246e8cb49e9e3013843076639972882db8028b5eaceb5feba11ea803494b","source":{"kind":"arxiv","id":"2112.00582","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.00582","created_at":"2026-07-05T03:36:48Z"},{"alias_kind":"arxiv_version","alias_value":"2112.00582v1","created_at":"2026-07-05T03:36:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.00582","created_at":"2026-07-05T03:36:48Z"},{"alias_kind":"pith_short_12","alias_value":"OZ2CI3UMWSPJ","created_at":"2026-07-05T03:36:48Z"},{"alias_kind":"pith_short_16","alias_value":"OZ2CI3UMWSPJ4MAT","created_at":"2026-07-05T03:36:48Z"},{"alias_kind":"pith_short_8","alias_value":"OZ2CI3UM","created_at":"2026-07-05T03:36:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:OZ2CI3UMWSPJ4MATQQYHMY4ZOK","target":"record","payload":{"canonical_record":{"source":{"id":"2112.00582","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-12-01T15:53:58Z","cross_cats_sorted":[],"title_canon_sha256":"f098c883a23ccface85441301705e596f0a7869c6963efe7763d1ab2e1443c66","abstract_canon_sha256":"1e64f165a20473b586113f962f033de91ce5336cf6573927e458fcf4f926e170"},"schema_version":"1.0"},"canonical_sha256":"7674246e8cb49e9e3013843076639972882db8028b5eaceb5feba11ea803494b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:36:48.188348Z","signature_b64":"niILOkJ/V8FI/goz8QQ8Bt/m4463u1Ekoukx4/jWn3Se1rus53+zKDq+Q+sjdUGNuqzPWW3InpNwFXmFGlHyAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7674246e8cb49e9e3013843076639972882db8028b5eaceb5feba11ea803494b","last_reissued_at":"2026-07-05T03:36:48.187877Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:36:48.187877Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2112.00582","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":"2026-07-05T03:36:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IT5Z90bdNX69qDy9NvfR/QVKqC0P2AxvseWixugfeXodQ4C1O7pioZqAsr7CfnJGQrJgXDTMb9VpFY8hfpVHBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T22:39:08.823558Z"},"content_sha256":"9508b42badc3d04333b1b1d461c3ec330c56c45b84d2e88add98821ad6b94bb3","schema_version":"1.0","event_id":"sha256:9508b42badc3d04333b1b1d461c3ec330c56c45b84d2e88add98821ad6b94bb3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:OZ2CI3UMWSPJ4MATQQYHMY4ZOK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Transformer-based Network for RGB-D Saliency Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Huchuan Lu, James Elder, Lu Zhang, Xu Jia, Yue Wang, Yuke Li","submitted_at":"2021-12-01T15:53:58Z","abstract_excerpt":"RGB-D saliency detection integrates information from both RGB images and depth maps to improve prediction of salient regions under challenging conditions. The key to RGB-D saliency detection is to fully mine and fuse information at multiple scales across the two modalities. Previous approaches tend to apply the multi-scale and multi-modal fusion separately via local operations, which fails to capture long-range dependencies. Here we propose a transformer-based network to address this issue. Our proposed architecture is composed of two modules: a transformer-based within-modality feature enhanc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.00582","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/2112.00582/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":"2026-07-05T03:36:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cwPX4DzTko2HVbNkWzY2uxploNR3sfv/QSOap1z5rCg0DYH28Db0cpHd7BMnPMeHLJ2yBuVwDsrGYZadKRpUBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T22:39:08.824056Z"},"content_sha256":"6f60dd23d8f14c5475daa321993d477c8effa0a2f62c3f43a8e85d778871c897","schema_version":"1.0","event_id":"sha256:6f60dd23d8f14c5475daa321993d477c8effa0a2f62c3f43a8e85d778871c897"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OZ2CI3UMWSPJ4MATQQYHMY4ZOK/bundle.json","state_url":"https://pith.science/pith/OZ2CI3UMWSPJ4MATQQYHMY4ZOK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OZ2CI3UMWSPJ4MATQQYHMY4ZOK/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":"2026-08-23T22:39:08Z","links":{"resolver":"https://pith.science/pith/OZ2CI3UMWSPJ4MATQQYHMY4ZOK","bundle":"https://pith.science/pith/OZ2CI3UMWSPJ4MATQQYHMY4ZOK/bundle.json","state":"https://pith.science/pith/OZ2CI3UMWSPJ4MATQQYHMY4ZOK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OZ2CI3UMWSPJ4MATQQYHMY4ZOK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:OZ2CI3UMWSPJ4MATQQYHMY4ZOK","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":"1e64f165a20473b586113f962f033de91ce5336cf6573927e458fcf4f926e170","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-12-01T15:53:58Z","title_canon_sha256":"f098c883a23ccface85441301705e596f0a7869c6963efe7763d1ab2e1443c66"},"schema_version":"1.0","source":{"id":"2112.00582","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.00582","created_at":"2026-07-05T03:36:48Z"},{"alias_kind":"arxiv_version","alias_value":"2112.00582v1","created_at":"2026-07-05T03:36:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.00582","created_at":"2026-07-05T03:36:48Z"},{"alias_kind":"pith_short_12","alias_value":"OZ2CI3UMWSPJ","created_at":"2026-07-05T03:36:48Z"},{"alias_kind":"pith_short_16","alias_value":"OZ2CI3UMWSPJ4MAT","created_at":"2026-07-05T03:36:48Z"},{"alias_kind":"pith_short_8","alias_value":"OZ2CI3UM","created_at":"2026-07-05T03:36:48Z"}],"graph_snapshots":[{"event_id":"sha256:6f60dd23d8f14c5475daa321993d477c8effa0a2f62c3f43a8e85d778871c897","target":"graph","created_at":"2026-07-05T03:36:48Z","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/2112.00582/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"RGB-D saliency detection integrates information from both RGB images and depth maps to improve prediction of salient regions under challenging conditions. The key to RGB-D saliency detection is to fully mine and fuse information at multiple scales across the two modalities. Previous approaches tend to apply the multi-scale and multi-modal fusion separately via local operations, which fails to capture long-range dependencies. Here we propose a transformer-based network to address this issue. Our proposed architecture is composed of two modules: a transformer-based within-modality feature enhanc","authors_text":"Huchuan Lu, James Elder, Lu Zhang, Xu Jia, Yue Wang, Yuke Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-12-01T15:53:58Z","title":"Transformer-based Network for RGB-D Saliency Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.00582","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":"sha256:9508b42badc3d04333b1b1d461c3ec330c56c45b84d2e88add98821ad6b94bb3","target":"record","created_at":"2026-07-05T03:36:48Z","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":"1e64f165a20473b586113f962f033de91ce5336cf6573927e458fcf4f926e170","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-12-01T15:53:58Z","title_canon_sha256":"f098c883a23ccface85441301705e596f0a7869c6963efe7763d1ab2e1443c66"},"schema_version":"1.0","source":{"id":"2112.00582","kind":"arxiv","version":1}},"canonical_sha256":"7674246e8cb49e9e3013843076639972882db8028b5eaceb5feba11ea803494b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7674246e8cb49e9e3013843076639972882db8028b5eaceb5feba11ea803494b","first_computed_at":"2026-07-05T03:36:48.187877Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:36:48.187877Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"niILOkJ/V8FI/goz8QQ8Bt/m4463u1Ekoukx4/jWn3Se1rus53+zKDq+Q+sjdUGNuqzPWW3InpNwFXmFGlHyAw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:36:48.188348Z","signed_message":"canonical_sha256_bytes"},"source_id":"2112.00582","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9508b42badc3d04333b1b1d461c3ec330c56c45b84d2e88add98821ad6b94bb3","sha256:6f60dd23d8f14c5475daa321993d477c8effa0a2f62c3f43a8e85d778871c897"],"state_sha256":"cec7c6e190e96aca046636019002c35c4c8836b3b87f4e29055ba03a71dcd864"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VnHYooSPIzTQvNnL2GH4DfXofA3u8rvNbpiV5W+jTw8GjvdHKUrzDqkntF5kCZOX7iinjutdYNyS/5fM8+vAAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T22:39:08.828809Z","bundle_sha256":"ad6971ca103c20dec8c5ca1bebdf31ff23aed30bc86e45e45f85677edc71c930"}}