{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:BGIGXCWEEM45KU7UCYGRUMEKEA","short_pith_number":"pith:BGIGXCWE","canonical_record":{"source":{"id":"2412.00155","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-29T07:45:24Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c4ce7fbff8af3bac1c9c7fea57ff4eac813b12589c25a6eaf9450b99b12cb31a","abstract_canon_sha256":"cd3e95b33e1faa754f770dafa62e1d02f16f5bc3490372658136954e8ce0a32a"},"schema_version":"1.0"},"canonical_sha256":"09906b8ac42339d553f4160d1a308a202f70639f5554518bd2add952e36304ac","source":{"kind":"arxiv","id":"2412.00155","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.00155","created_at":"2026-07-05T10:26:41Z"},{"alias_kind":"arxiv_version","alias_value":"2412.00155v2","created_at":"2026-07-05T10:26:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.00155","created_at":"2026-07-05T10:26:41Z"},{"alias_kind":"pith_short_12","alias_value":"BGIGXCWEEM45","created_at":"2026-07-05T10:26:41Z"},{"alias_kind":"pith_short_16","alias_value":"BGIGXCWEEM45KU7U","created_at":"2026-07-05T10:26:41Z"},{"alias_kind":"pith_short_8","alias_value":"BGIGXCWE","created_at":"2026-07-05T10:26:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:BGIGXCWEEM45KU7UCYGRUMEKEA","target":"record","payload":{"canonical_record":{"source":{"id":"2412.00155","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-29T07:45:24Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c4ce7fbff8af3bac1c9c7fea57ff4eac813b12589c25a6eaf9450b99b12cb31a","abstract_canon_sha256":"cd3e95b33e1faa754f770dafa62e1d02f16f5bc3490372658136954e8ce0a32a"},"schema_version":"1.0"},"canonical_sha256":"09906b8ac42339d553f4160d1a308a202f70639f5554518bd2add952e36304ac","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:26:41.912073Z","signature_b64":"kOX8zriHiKexG9BdRTwKAutTMz16Paguq0Fi9CKueU0m9maX8ISdJ3HYRYUyzgDeaspAb/8+8n5hmSJhUPlxCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"09906b8ac42339d553f4160d1a308a202f70639f5554518bd2add952e36304ac","last_reissued_at":"2026-07-05T10:26:41.911201Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:26:41.911201Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.00155","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":"2026-07-05T10:26:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QAHOVlmc38tU/VwY76QLpRoMqlpwUFhhfqPBmW3MDcgoSKVZkyz8+juJY50aMMRLAymUKb8SdIRSgoy3zSdzCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T07:06:34.574922Z"},"content_sha256":"8039342633b9d2f4281273ce9d888a0bf77051aa5723b366236e1e736e79e3ea","schema_version":"1.0","event_id":"sha256:8039342633b9d2f4281273ce9d888a0bf77051aa5723b366236e1e736e79e3ea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:BGIGXCWEEM45KU7UCYGRUMEKEA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"T-3DGS: Removing Transient Objects for 3D Scene Reconstruction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Alexander Markin, Artem Komarichev, Evgeny Burnaev, Peter Wonka, Ruslan Rakhimov, Vadim Pryadilshchikov","submitted_at":"2024-11-29T07:45:24Z","abstract_excerpt":"Transient objects in video sequences can significantly degrade the quality of 3D scene reconstructions. To address this challenge, we propose T-3DGS, a novel framework that robustly filters out transient distractors during 3D reconstruction using Gaussian Splatting. Our framework consists of two steps. First, we employ an unsupervised classification network that distinguishes transient objects from static scene elements by leveraging their distinct training dynamics within the reconstruction process. Second, we refine these initial detections by integrating an off-the-shelf segmentation method"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.00155","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/2412.00155/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":"2026-07-05T10:26:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p/J4Pi6JntCD7NHThqyUrafYtvlM3MqYI4/cg+Qheg+VG2F0uWbIOQEBB7wFkmPSKMwcTzVG/FZyvXbkccThAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T07:06:34.575460Z"},"content_sha256":"ecf595f150d43e79af762f4a115a6f2179d41f6eed837e5551dbd9e4955a62c9","schema_version":"1.0","event_id":"sha256:ecf595f150d43e79af762f4a115a6f2179d41f6eed837e5551dbd9e4955a62c9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BGIGXCWEEM45KU7UCYGRUMEKEA/bundle.json","state_url":"https://pith.science/pith/BGIGXCWEEM45KU7UCYGRUMEKEA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BGIGXCWEEM45KU7UCYGRUMEKEA/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":"2026-08-10T07:06:34Z","links":{"resolver":"https://pith.science/pith/BGIGXCWEEM45KU7UCYGRUMEKEA","bundle":"https://pith.science/pith/BGIGXCWEEM45KU7UCYGRUMEKEA/bundle.json","state":"https://pith.science/pith/BGIGXCWEEM45KU7UCYGRUMEKEA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BGIGXCWEEM45KU7UCYGRUMEKEA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BGIGXCWEEM45KU7UCYGRUMEKEA","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":"cd3e95b33e1faa754f770dafa62e1d02f16f5bc3490372658136954e8ce0a32a","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-29T07:45:24Z","title_canon_sha256":"c4ce7fbff8af3bac1c9c7fea57ff4eac813b12589c25a6eaf9450b99b12cb31a"},"schema_version":"1.0","source":{"id":"2412.00155","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.00155","created_at":"2026-07-05T10:26:41Z"},{"alias_kind":"arxiv_version","alias_value":"2412.00155v2","created_at":"2026-07-05T10:26:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.00155","created_at":"2026-07-05T10:26:41Z"},{"alias_kind":"pith_short_12","alias_value":"BGIGXCWEEM45","created_at":"2026-07-05T10:26:41Z"},{"alias_kind":"pith_short_16","alias_value":"BGIGXCWEEM45KU7U","created_at":"2026-07-05T10:26:41Z"},{"alias_kind":"pith_short_8","alias_value":"BGIGXCWE","created_at":"2026-07-05T10:26:41Z"}],"graph_snapshots":[{"event_id":"sha256:ecf595f150d43e79af762f4a115a6f2179d41f6eed837e5551dbd9e4955a62c9","target":"graph","created_at":"2026-07-05T10:26:41Z","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/2412.00155/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Transient objects in video sequences can significantly degrade the quality of 3D scene reconstructions. To address this challenge, we propose T-3DGS, a novel framework that robustly filters out transient distractors during 3D reconstruction using Gaussian Splatting. Our framework consists of two steps. First, we employ an unsupervised classification network that distinguishes transient objects from static scene elements by leveraging their distinct training dynamics within the reconstruction process. Second, we refine these initial detections by integrating an off-the-shelf segmentation method","authors_text":"Alexander Markin, Artem Komarichev, Evgeny Burnaev, Peter Wonka, Ruslan Rakhimov, Vadim Pryadilshchikov","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-29T07:45:24Z","title":"T-3DGS: Removing Transient Objects for 3D Scene Reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.00155","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":"sha256:8039342633b9d2f4281273ce9d888a0bf77051aa5723b366236e1e736e79e3ea","target":"record","created_at":"2026-07-05T10:26:41Z","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":"cd3e95b33e1faa754f770dafa62e1d02f16f5bc3490372658136954e8ce0a32a","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-29T07:45:24Z","title_canon_sha256":"c4ce7fbff8af3bac1c9c7fea57ff4eac813b12589c25a6eaf9450b99b12cb31a"},"schema_version":"1.0","source":{"id":"2412.00155","kind":"arxiv","version":2}},"canonical_sha256":"09906b8ac42339d553f4160d1a308a202f70639f5554518bd2add952e36304ac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"09906b8ac42339d553f4160d1a308a202f70639f5554518bd2add952e36304ac","first_computed_at":"2026-07-05T10:26:41.911201Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:26:41.911201Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kOX8zriHiKexG9BdRTwKAutTMz16Paguq0Fi9CKueU0m9maX8ISdJ3HYRYUyzgDeaspAb/8+8n5hmSJhUPlxCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:26:41.912073Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.00155","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8039342633b9d2f4281273ce9d888a0bf77051aa5723b366236e1e736e79e3ea","sha256:ecf595f150d43e79af762f4a115a6f2179d41f6eed837e5551dbd9e4955a62c9"],"state_sha256":"f6e30f0e45e0fd5101a728a8fa2b3d0be10f0d5eacfd6f4c9bf52cb8d378ec19"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NMmHe9xBgGoi0mwARGVvYoRVX+4xL58sruw/tENMcOzp5zNhJ24jIF16sgRVZ2xrMvF85bKfq6WylN6YBo/CBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T07:06:34.580566Z","bundle_sha256":"608b4f91453746d99bf81e05fabd4d410c7e3929ed73a1569b184586251ce7b7"}}