{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:ZQ43E4SBFKD7JGVJ4BDGU2UBHW","short_pith_number":"pith:ZQ43E4SB","canonical_record":{"source":{"id":"2103.15369","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-03-29T06:47:01Z","cross_cats_sorted":["cs.AI","cs.GR"],"title_canon_sha256":"4a1da1f497aada2ef12959f6bbbb29d1e0c3f0bcdf9485b4b89e8f2bb885bac3","abstract_canon_sha256":"b7e3f5da384e3aa744aeaa1e8d7dc4b53fb3b5205df8c7db95585a306029528d"},"schema_version":"1.0"},"canonical_sha256":"cc39b272412a87f49aa9e0466a6a813d9060b553a3b3a295b35aab3851903f0a","source":{"kind":"arxiv","id":"2103.15369","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.15369","created_at":"2026-07-05T02:27:05Z"},{"alias_kind":"arxiv_version","alias_value":"2103.15369v1","created_at":"2026-07-05T02:27:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.15369","created_at":"2026-07-05T02:27:05Z"},{"alias_kind":"pith_short_12","alias_value":"ZQ43E4SBFKD7","created_at":"2026-07-05T02:27:05Z"},{"alias_kind":"pith_short_16","alias_value":"ZQ43E4SBFKD7JGVJ","created_at":"2026-07-05T02:27:05Z"},{"alias_kind":"pith_short_8","alias_value":"ZQ43E4SB","created_at":"2026-07-05T02:27:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:ZQ43E4SBFKD7JGVJ4BDGU2UBHW","target":"record","payload":{"canonical_record":{"source":{"id":"2103.15369","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-03-29T06:47:01Z","cross_cats_sorted":["cs.AI","cs.GR"],"title_canon_sha256":"4a1da1f497aada2ef12959f6bbbb29d1e0c3f0bcdf9485b4b89e8f2bb885bac3","abstract_canon_sha256":"b7e3f5da384e3aa744aeaa1e8d7dc4b53fb3b5205df8c7db95585a306029528d"},"schema_version":"1.0"},"canonical_sha256":"cc39b272412a87f49aa9e0466a6a813d9060b553a3b3a295b35aab3851903f0a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:27:05.297963Z","signature_b64":"trV4pdMUo7GNWYYJqe9jb8DcXyCyPftH0yRAb3O20+dP2vLPH25aP1fl3xrLuo1GLBQzzAsn/cyb0vM/iSaXAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cc39b272412a87f49aa9e0466a6a813d9060b553a3b3a295b35aab3851903f0a","last_reissued_at":"2026-07-05T02:27:05.297485Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:27:05.297485Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2103.15369","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":"2026-07-05T02:27:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qEAZpLOhHyKUGvV/QEjhuP5SoYPGpms46t5Yo8+JBAQbsFR1hNaX1rC2gK8Y+NvLUvFb1rdw4VjwlbotVd76CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:21:41.672906Z"},"content_sha256":"f9a18e23d44bde64f931c56d4d0cf550abad9ba55e0dfa0b717f15a601c3771c","schema_version":"1.0","event_id":"sha256:f9a18e23d44bde64f931c56d4d0cf550abad9ba55e0dfa0b717f15a601c3771c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:ZQ43E4SBFKD7JGVJ4BDGU2UBHW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Contextual Scene Augmentation and Synthesis via GSACNet","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.GR"],"primary_cat":"cs.CV","authors_text":"Allen Y. Yang, Flaviano Christian Reyes, Luisa Caldas, Mohammad Keshavarzi, Oladapo Afolabi, Ritika Shrivastava","submitted_at":"2021-03-29T06:47:01Z","abstract_excerpt":"Indoor scene augmentation has become an emerging topic in the field of computer vision and graphics with applications in augmented and virtual reality. However, current state-of-the-art systems using deep neural networks require large datasets for training. In this paper we introduce GSACNet, a contextual scene augmentation system that can be trained with limited scene priors. GSACNet utilizes a novel parametric data augmentation method combined with a Graph Attention and Siamese network architecture followed by an Autoencoder network to facilitate training with small datasets. We show the eff"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.15369","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/2103.15369/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":"2026-07-05T02:27:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ti0e6q5nocG6UH9MmspaasgEsf+ffNeH8xC7L0ghE3sLW/upSr6mGK+s7AgROIWWEhnCHVoQZN7wOkD2bpsPDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:21:41.673719Z"},"content_sha256":"b7782ff7d7277ed9ef74363f3e18804959e72cc8835947a448c1c07df49781c2","schema_version":"1.0","event_id":"sha256:b7782ff7d7277ed9ef74363f3e18804959e72cc8835947a448c1c07df49781c2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZQ43E4SBFKD7JGVJ4BDGU2UBHW/bundle.json","state_url":"https://pith.science/pith/ZQ43E4SBFKD7JGVJ4BDGU2UBHW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZQ43E4SBFKD7JGVJ4BDGU2UBHW/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":"2026-08-05T15:21:41Z","links":{"resolver":"https://pith.science/pith/ZQ43E4SBFKD7JGVJ4BDGU2UBHW","bundle":"https://pith.science/pith/ZQ43E4SBFKD7JGVJ4BDGU2UBHW/bundle.json","state":"https://pith.science/pith/ZQ43E4SBFKD7JGVJ4BDGU2UBHW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZQ43E4SBFKD7JGVJ4BDGU2UBHW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:ZQ43E4SBFKD7JGVJ4BDGU2UBHW","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":"b7e3f5da384e3aa744aeaa1e8d7dc4b53fb3b5205df8c7db95585a306029528d","cross_cats_sorted":["cs.AI","cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-03-29T06:47:01Z","title_canon_sha256":"4a1da1f497aada2ef12959f6bbbb29d1e0c3f0bcdf9485b4b89e8f2bb885bac3"},"schema_version":"1.0","source":{"id":"2103.15369","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.15369","created_at":"2026-07-05T02:27:05Z"},{"alias_kind":"arxiv_version","alias_value":"2103.15369v1","created_at":"2026-07-05T02:27:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.15369","created_at":"2026-07-05T02:27:05Z"},{"alias_kind":"pith_short_12","alias_value":"ZQ43E4SBFKD7","created_at":"2026-07-05T02:27:05Z"},{"alias_kind":"pith_short_16","alias_value":"ZQ43E4SBFKD7JGVJ","created_at":"2026-07-05T02:27:05Z"},{"alias_kind":"pith_short_8","alias_value":"ZQ43E4SB","created_at":"2026-07-05T02:27:05Z"}],"graph_snapshots":[{"event_id":"sha256:b7782ff7d7277ed9ef74363f3e18804959e72cc8835947a448c1c07df49781c2","target":"graph","created_at":"2026-07-05T02:27:05Z","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/2103.15369/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Indoor scene augmentation has become an emerging topic in the field of computer vision and graphics with applications in augmented and virtual reality. However, current state-of-the-art systems using deep neural networks require large datasets for training. In this paper we introduce GSACNet, a contextual scene augmentation system that can be trained with limited scene priors. GSACNet utilizes a novel parametric data augmentation method combined with a Graph Attention and Siamese network architecture followed by an Autoencoder network to facilitate training with small datasets. We show the eff","authors_text":"Allen Y. Yang, Flaviano Christian Reyes, Luisa Caldas, Mohammad Keshavarzi, Oladapo Afolabi, Ritika Shrivastava","cross_cats":["cs.AI","cs.GR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-03-29T06:47:01Z","title":"Contextual Scene Augmentation and Synthesis via GSACNet"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.15369","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:f9a18e23d44bde64f931c56d4d0cf550abad9ba55e0dfa0b717f15a601c3771c","target":"record","created_at":"2026-07-05T02:27:05Z","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":"b7e3f5da384e3aa744aeaa1e8d7dc4b53fb3b5205df8c7db95585a306029528d","cross_cats_sorted":["cs.AI","cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-03-29T06:47:01Z","title_canon_sha256":"4a1da1f497aada2ef12959f6bbbb29d1e0c3f0bcdf9485b4b89e8f2bb885bac3"},"schema_version":"1.0","source":{"id":"2103.15369","kind":"arxiv","version":1}},"canonical_sha256":"cc39b272412a87f49aa9e0466a6a813d9060b553a3b3a295b35aab3851903f0a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cc39b272412a87f49aa9e0466a6a813d9060b553a3b3a295b35aab3851903f0a","first_computed_at":"2026-07-05T02:27:05.297485Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:27:05.297485Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"trV4pdMUo7GNWYYJqe9jb8DcXyCyPftH0yRAb3O20+dP2vLPH25aP1fl3xrLuo1GLBQzzAsn/cyb0vM/iSaXAA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:27:05.297963Z","signed_message":"canonical_sha256_bytes"},"source_id":"2103.15369","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f9a18e23d44bde64f931c56d4d0cf550abad9ba55e0dfa0b717f15a601c3771c","sha256:b7782ff7d7277ed9ef74363f3e18804959e72cc8835947a448c1c07df49781c2"],"state_sha256":"da86e4ae8d754ed55b61f1144a11bf8e32d73011c55ab102a13e6575c6bc13b2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lev/SqfidKXcEbxKhZZBWNec6/NsdmHQS4IRSYKyJcIG+Kebdlf02zZpUkixa2e6RxiOEJBcQSFiUaYzeJ5PCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T15:21:41.679278Z","bundle_sha256":"e4e8d203d85eb9489b841bf6b3d487100129bf17371321669d09be278636556f"}}