{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:MH3P2X2IDIJ5G2WDM2BEH7KZ5Z","short_pith_number":"pith:MH3P2X2I","canonical_record":{"source":{"id":"2403.08498","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-13T13:06:31Z","cross_cats_sorted":[],"title_canon_sha256":"8386be451ccd71699d8c7d1d627bc9470fd6cf66335a062bf66e9c9b020c0ac8","abstract_canon_sha256":"eb74348c22146ec72f2285b61eb96a83469ea316bddbb82e8eb908451bafa8c5"},"schema_version":"1.0"},"canonical_sha256":"61f6fd5f481a13d36ac3668243fd59ee7689897e1105c63d19553ff5e7730b31","source":{"kind":"arxiv","id":"2403.08498","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.08498","created_at":"2026-07-05T09:03:50Z"},{"alias_kind":"arxiv_version","alias_value":"2403.08498v2","created_at":"2026-07-05T09:03:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.08498","created_at":"2026-07-05T09:03:50Z"},{"alias_kind":"pith_short_12","alias_value":"MH3P2X2IDIJ5","created_at":"2026-07-05T09:03:50Z"},{"alias_kind":"pith_short_16","alias_value":"MH3P2X2IDIJ5G2WD","created_at":"2026-07-05T09:03:50Z"},{"alias_kind":"pith_short_8","alias_value":"MH3P2X2I","created_at":"2026-07-05T09:03:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:MH3P2X2IDIJ5G2WDM2BEH7KZ5Z","target":"record","payload":{"canonical_record":{"source":{"id":"2403.08498","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-13T13:06:31Z","cross_cats_sorted":[],"title_canon_sha256":"8386be451ccd71699d8c7d1d627bc9470fd6cf66335a062bf66e9c9b020c0ac8","abstract_canon_sha256":"eb74348c22146ec72f2285b61eb96a83469ea316bddbb82e8eb908451bafa8c5"},"schema_version":"1.0"},"canonical_sha256":"61f6fd5f481a13d36ac3668243fd59ee7689897e1105c63d19553ff5e7730b31","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:03:50.510541Z","signature_b64":"8O9vs5Z2TD58WItMhb2FjFC8czBQd/CJeKvEMoHGNiCMtbj0tBsxqV+3R2MpWaMrCL0ZAkbi0HON4pamkgX/Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"61f6fd5f481a13d36ac3668243fd59ee7689897e1105c63d19553ff5e7730b31","last_reissued_at":"2026-07-05T09:03:50.510055Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:03:50.510055Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.08498","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":"2026-07-05T09:03:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eN1GAcAwFoZrDhtFkWqiEM8xU6SCFiNHkN132ZxMWGFXD3jQfRTDayubnuAy4TgSxdZZhVPqtKEK//GuVuwlBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T12:24:26.171717Z"},"content_sha256":"7309e0fb513b13688bd732742916662fe37cd88c9bde7c848c275362c8385143","schema_version":"1.0","event_id":"sha256:7309e0fb513b13688bd732742916662fe37cd88c9bde7c848c275362c8385143"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:MH3P2X2IDIJ5G2WDM2BEH7KZ5Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Gaussian Splatting in Style","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abhishek Saroha, Cecilia Curreli, Daniel Cremers, Dominik Muhle, Mariia Gladkova, Tarun Yenamandra","submitted_at":"2024-03-13T13:06:31Z","abstract_excerpt":"3D scene stylization extends the work of neural style transfer to 3D. A vital challenge in this problem is to maintain the uniformity of the stylized appearance across multiple views. A vast majority of the previous works achieve this by training a 3D model for every stylized image and a set of multi-view images. In contrast, we propose a novel architecture trained on a collection of style images that, at test time, produces real time high-quality stylized novel views. We choose the underlying 3D scene representation for our model as 3D Gaussian splatting. We take the 3D Gaussians and process "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.08498","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/2403.08498/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":"2026-07-05T09:03:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nLNwcXfzC45HMUVSNoLqO09uNIvHd+t9h9SiKM1FrcCMU3rgim3MR9FHxVi02+Qa9KBU6XWmAeVNe9kwPYZaCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T12:24:26.172091Z"},"content_sha256":"6a189e83f45a777541e18297d5b4731a3bbac4dff4f2ecf8473d548577e8a9fa","schema_version":"1.0","event_id":"sha256:6a189e83f45a777541e18297d5b4731a3bbac4dff4f2ecf8473d548577e8a9fa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MH3P2X2IDIJ5G2WDM2BEH7KZ5Z/bundle.json","state_url":"https://pith.science/pith/MH3P2X2IDIJ5G2WDM2BEH7KZ5Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MH3P2X2IDIJ5G2WDM2BEH7KZ5Z/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":"2026-07-06T12:24:26Z","links":{"resolver":"https://pith.science/pith/MH3P2X2IDIJ5G2WDM2BEH7KZ5Z","bundle":"https://pith.science/pith/MH3P2X2IDIJ5G2WDM2BEH7KZ5Z/bundle.json","state":"https://pith.science/pith/MH3P2X2IDIJ5G2WDM2BEH7KZ5Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MH3P2X2IDIJ5G2WDM2BEH7KZ5Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MH3P2X2IDIJ5G2WDM2BEH7KZ5Z","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":"eb74348c22146ec72f2285b61eb96a83469ea316bddbb82e8eb908451bafa8c5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-13T13:06:31Z","title_canon_sha256":"8386be451ccd71699d8c7d1d627bc9470fd6cf66335a062bf66e9c9b020c0ac8"},"schema_version":"1.0","source":{"id":"2403.08498","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.08498","created_at":"2026-07-05T09:03:50Z"},{"alias_kind":"arxiv_version","alias_value":"2403.08498v2","created_at":"2026-07-05T09:03:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.08498","created_at":"2026-07-05T09:03:50Z"},{"alias_kind":"pith_short_12","alias_value":"MH3P2X2IDIJ5","created_at":"2026-07-05T09:03:50Z"},{"alias_kind":"pith_short_16","alias_value":"MH3P2X2IDIJ5G2WD","created_at":"2026-07-05T09:03:50Z"},{"alias_kind":"pith_short_8","alias_value":"MH3P2X2I","created_at":"2026-07-05T09:03:50Z"}],"graph_snapshots":[{"event_id":"sha256:6a189e83f45a777541e18297d5b4731a3bbac4dff4f2ecf8473d548577e8a9fa","target":"graph","created_at":"2026-07-05T09:03:50Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2403.08498/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"3D scene stylization extends the work of neural style transfer to 3D. A vital challenge in this problem is to maintain the uniformity of the stylized appearance across multiple views. A vast majority of the previous works achieve this by training a 3D model for every stylized image and a set of multi-view images. In contrast, we propose a novel architecture trained on a collection of style images that, at test time, produces real time high-quality stylized novel views. We choose the underlying 3D scene representation for our model as 3D Gaussian splatting. We take the 3D Gaussians and process ","authors_text":"Abhishek Saroha, Cecilia Curreli, Daniel Cremers, Dominik Muhle, Mariia Gladkova, Tarun Yenamandra","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-13T13:06:31Z","title":"Gaussian Splatting in Style"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.08498","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":"sha256:7309e0fb513b13688bd732742916662fe37cd88c9bde7c848c275362c8385143","target":"record","created_at":"2026-07-05T09:03:50Z","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":"eb74348c22146ec72f2285b61eb96a83469ea316bddbb82e8eb908451bafa8c5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-13T13:06:31Z","title_canon_sha256":"8386be451ccd71699d8c7d1d627bc9470fd6cf66335a062bf66e9c9b020c0ac8"},"schema_version":"1.0","source":{"id":"2403.08498","kind":"arxiv","version":2}},"canonical_sha256":"61f6fd5f481a13d36ac3668243fd59ee7689897e1105c63d19553ff5e7730b31","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"61f6fd5f481a13d36ac3668243fd59ee7689897e1105c63d19553ff5e7730b31","first_computed_at":"2026-07-05T09:03:50.510055Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:03:50.510055Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8O9vs5Z2TD58WItMhb2FjFC8czBQd/CJeKvEMoHGNiCMtbj0tBsxqV+3R2MpWaMrCL0ZAkbi0HON4pamkgX/Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:03:50.510541Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.08498","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7309e0fb513b13688bd732742916662fe37cd88c9bde7c848c275362c8385143","sha256:6a189e83f45a777541e18297d5b4731a3bbac4dff4f2ecf8473d548577e8a9fa"],"state_sha256":"7ce2b9925c9258ac8d88f4ccf3e471e19f7deefc6f6b498a4a975194d6732e46"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q9uM4OGhp/Es3AjHw1vbbM/Cof6LFU3ZEGiRlX5dVAuN0AohGDPebHxrEtu2itfQhDtwUwEW80ZJaEqUsb+cDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T12:24:26.174087Z","bundle_sha256":"248fbf496bb183686231b86dfe5b4072e71672074e2dc89f9f2c8d400b0fd537"}}