{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:W45BC7OTR2T33L56T47BXYKEK6","short_pith_number":"pith:W45BC7OT","canonical_record":{"source":{"id":"1812.08350","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2018-12-20T03:49:49Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"2c9d9fe5bde6335376396c88795aa00dfa94e161d3586e8d76de9379212b0272","abstract_canon_sha256":"7d2ff0525f46bcf5b5c378329aec110fbb89e194e8795cd82cd39dac74de5c4b"},"schema_version":"1.0"},"canonical_sha256":"b73a117dd38ea7bdafbe9f3e1be14457b6c1adf212a379b7e681965f1dfdd2a7","source":{"kind":"arxiv","id":"1812.08350","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.08350","created_at":"2026-05-17T23:48:50Z"},{"alias_kind":"arxiv_version","alias_value":"1812.08350v2","created_at":"2026-05-17T23:48:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.08350","created_at":"2026-05-17T23:48:50Z"},{"alias_kind":"pith_short_12","alias_value":"W45BC7OTR2T3","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"W45BC7OTR2T33L56","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"W45BC7OT","created_at":"2026-05-18T12:32:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:W45BC7OTR2T33L56T47BXYKEK6","target":"record","payload":{"canonical_record":{"source":{"id":"1812.08350","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2018-12-20T03:49:49Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"2c9d9fe5bde6335376396c88795aa00dfa94e161d3586e8d76de9379212b0272","abstract_canon_sha256":"7d2ff0525f46bcf5b5c378329aec110fbb89e194e8795cd82cd39dac74de5c4b"},"schema_version":"1.0"},"canonical_sha256":"b73a117dd38ea7bdafbe9f3e1be14457b6c1adf212a379b7e681965f1dfdd2a7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:50.361094Z","signature_b64":"/OUxcVkw2HFUnaEspWs1OYosPvO9Hh0/sav87sbAEQ7pi6xMG0YwMDziAQy15s81KY5GA5fZGWzbcy8Cv/+HBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b73a117dd38ea7bdafbe9f3e1be14457b6c1adf212a379b7e681965f1dfdd2a7","last_reissued_at":"2026-05-17T23:48:50.360403Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:50.360403Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.08350","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":"2026-05-17T23:48:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LYvkLNhI4RELPLKSfVfdf27cXwYN10zztsu0AgglbKPZ2XKH7Y+p48jV2igSo+wGq389HSg7woRi0x48SqrtAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T21:04:25.047085Z"},"content_sha256":"d73123048e04c4493488cbf3babd0b5e12241e74134ead3ae3852dc01f592ff4","schema_version":"1.0","event_id":"sha256:d73123048e04c4493488cbf3babd0b5e12241e74134ead3ae3852dc01f592ff4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:W45BC7OTR2T33L56T47BXYKEK6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Plug-and-Play: Improve Depth Estimation via Sparse Data Propagation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Fu-En Wang, Juan-Ting Lin, Min Sun, Tsun-Hsuan Wang, Wei-Chen Chiu, Yi-Hsuan Tsai","submitted_at":"2018-12-20T03:49:49Z","abstract_excerpt":"We propose a novel plug-and-play (PnP) module for improving depth prediction with taking arbitrary patterns of sparse depths as input. Given any pre-trained depth prediction model, our PnP module updates the intermediate feature map such that the model outputs new depths consistent with the given sparse depths. Our method requires no additional training and can be applied to practical applications such as leveraging both RGB and sparse LiDAR points to robustly estimate dense depth map. Our approach achieves consistent improvements on various state-of-the-art methods on indoor (i.e., NYU-v2) an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.08350","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":""},"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":"2026-05-17T23:48:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Fw/cvEE5VmGadrSwYbsPm4W7UMeX2nr9BJfOiB33qmA5Sx2vL/7qHs+gPsWFKbLpm193vwJdCJX3P18gFfK+AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T21:04:25.047646Z"},"content_sha256":"25ed9f2ea32db01838e0995d3f54d0e91b4cdc2fff50647b5aed22f1ec16f59c","schema_version":"1.0","event_id":"sha256:25ed9f2ea32db01838e0995d3f54d0e91b4cdc2fff50647b5aed22f1ec16f59c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W45BC7OTR2T33L56T47BXYKEK6/bundle.json","state_url":"https://pith.science/pith/W45BC7OTR2T33L56T47BXYKEK6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W45BC7OTR2T33L56T47BXYKEK6/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":"2026-05-25T21:04:25Z","links":{"resolver":"https://pith.science/pith/W45BC7OTR2T33L56T47BXYKEK6","bundle":"https://pith.science/pith/W45BC7OTR2T33L56T47BXYKEK6/bundle.json","state":"https://pith.science/pith/W45BC7OTR2T33L56T47BXYKEK6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W45BC7OTR2T33L56T47BXYKEK6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:W45BC7OTR2T33L56T47BXYKEK6","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":"7d2ff0525f46bcf5b5c378329aec110fbb89e194e8795cd82cd39dac74de5c4b","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2018-12-20T03:49:49Z","title_canon_sha256":"2c9d9fe5bde6335376396c88795aa00dfa94e161d3586e8d76de9379212b0272"},"schema_version":"1.0","source":{"id":"1812.08350","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.08350","created_at":"2026-05-17T23:48:50Z"},{"alias_kind":"arxiv_version","alias_value":"1812.08350v2","created_at":"2026-05-17T23:48:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.08350","created_at":"2026-05-17T23:48:50Z"},{"alias_kind":"pith_short_12","alias_value":"W45BC7OTR2T3","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"W45BC7OTR2T33L56","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"W45BC7OT","created_at":"2026-05-18T12:32:59Z"}],"graph_snapshots":[{"event_id":"sha256:25ed9f2ea32db01838e0995d3f54d0e91b4cdc2fff50647b5aed22f1ec16f59c","target":"graph","created_at":"2026-05-17T23:48:50Z","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"},"paper":{"abstract_excerpt":"We propose a novel plug-and-play (PnP) module for improving depth prediction with taking arbitrary patterns of sparse depths as input. Given any pre-trained depth prediction model, our PnP module updates the intermediate feature map such that the model outputs new depths consistent with the given sparse depths. Our method requires no additional training and can be applied to practical applications such as leveraging both RGB and sparse LiDAR points to robustly estimate dense depth map. Our approach achieves consistent improvements on various state-of-the-art methods on indoor (i.e., NYU-v2) an","authors_text":"Fu-En Wang, Juan-Ting Lin, Min Sun, Tsun-Hsuan Wang, Wei-Chen Chiu, Yi-Hsuan Tsai","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2018-12-20T03:49:49Z","title":"Plug-and-Play: Improve Depth Estimation via Sparse Data Propagation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.08350","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:d73123048e04c4493488cbf3babd0b5e12241e74134ead3ae3852dc01f592ff4","target":"record","created_at":"2026-05-17T23:48:50Z","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":"7d2ff0525f46bcf5b5c378329aec110fbb89e194e8795cd82cd39dac74de5c4b","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2018-12-20T03:49:49Z","title_canon_sha256":"2c9d9fe5bde6335376396c88795aa00dfa94e161d3586e8d76de9379212b0272"},"schema_version":"1.0","source":{"id":"1812.08350","kind":"arxiv","version":2}},"canonical_sha256":"b73a117dd38ea7bdafbe9f3e1be14457b6c1adf212a379b7e681965f1dfdd2a7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b73a117dd38ea7bdafbe9f3e1be14457b6c1adf212a379b7e681965f1dfdd2a7","first_computed_at":"2026-05-17T23:48:50.360403Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:50.360403Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/OUxcVkw2HFUnaEspWs1OYosPvO9Hh0/sav87sbAEQ7pi6xMG0YwMDziAQy15s81KY5GA5fZGWzbcy8Cv/+HBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:50.361094Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.08350","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d73123048e04c4493488cbf3babd0b5e12241e74134ead3ae3852dc01f592ff4","sha256:25ed9f2ea32db01838e0995d3f54d0e91b4cdc2fff50647b5aed22f1ec16f59c"],"state_sha256":"3edc1ac096cdcfe178811f2ef66985d8e17d75fcc9d77faedce1424d3c073129"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4+wrid8ekCy5iMOb26zu2uFxtxZs8ff5DHZ8kvyJ0ThPv1HMf+fm732dfPmqttLmu1UrUMbrASoaayHK1bfIAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T21:04:25.050748Z","bundle_sha256":"c5e19ef6efbd9742844b0ccf57c4515e7f9e4d829b3094e90968444b1ef48e7b"}}