{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:MS6ZYHM7LCCJRQCGLHRPGTKXDM","short_pith_number":"pith:MS6ZYHM7","canonical_record":{"source":{"id":"2012.09793","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-12-17T17:57:27Z","cross_cats_sorted":[],"title_canon_sha256":"e9d3f380a731b6719dabc819d6aa3b3bf83a615590d39c4aeb7f50cd1e84de77","abstract_canon_sha256":"96006126a88ca5c42d7e9335859b06c8a95d387754835224d34fba093922858f"},"schema_version":"1.0"},"canonical_sha256":"64bd9c1d9f588498c04659e2f34d571b04be37db777a493ce109267d9e0c2e32","source":{"kind":"arxiv","id":"2012.09793","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.09793","created_at":"2026-07-05T02:28:33Z"},{"alias_kind":"arxiv_version","alias_value":"2012.09793v2","created_at":"2026-07-05T02:28:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.09793","created_at":"2026-07-05T02:28:33Z"},{"alias_kind":"pith_short_12","alias_value":"MS6ZYHM7LCCJ","created_at":"2026-07-05T02:28:33Z"},{"alias_kind":"pith_short_16","alias_value":"MS6ZYHM7LCCJRQCG","created_at":"2026-07-05T02:28:33Z"},{"alias_kind":"pith_short_8","alias_value":"MS6ZYHM7","created_at":"2026-07-05T02:28:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:MS6ZYHM7LCCJRQCGLHRPGTKXDM","target":"record","payload":{"canonical_record":{"source":{"id":"2012.09793","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-12-17T17:57:27Z","cross_cats_sorted":[],"title_canon_sha256":"e9d3f380a731b6719dabc819d6aa3b3bf83a615590d39c4aeb7f50cd1e84de77","abstract_canon_sha256":"96006126a88ca5c42d7e9335859b06c8a95d387754835224d34fba093922858f"},"schema_version":"1.0"},"canonical_sha256":"64bd9c1d9f588498c04659e2f34d571b04be37db777a493ce109267d9e0c2e32","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:28:33.549180Z","signature_b64":"TgDSnOrnHAb/mZmAhGFWjPuwqGLTxNstUT0+XkjqEwbcaFYhpRtjRunE4s0eoOgF/m66K9+kVCmrZ1daxAUpCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"64bd9c1d9f588498c04659e2f34d571b04be37db777a493ce109267d9e0c2e32","last_reissued_at":"2026-07-05T02:28:33.548711Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:28:33.548711Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2012.09793","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":"2026-07-05T02:28:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Hp7+QfvK4uSS/NEQRPn9oFISFOZTVbdlulqZMP6nAqVSkjAzRA0bh/nFQUn7OdrSEO3QtefsxsZY+NzsjtI9Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:08:38.907090Z"},"content_sha256":"3c13401a500a48f55bb183d54beb49aad66e8823502920abba8c36066a7e580b","schema_version":"1.0","event_id":"sha256:3c13401a500a48f55bb183d54beb49aad66e8823502920abba8c36066a7e580b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:MS6ZYHM7LCCJRQCGLHRPGTKXDM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SceneFormer: Indoor Scene Generation with Transformers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chandan Yeshwanth, Matthias Nie{\\ss}ner, Xinpeng Wang","submitted_at":"2020-12-17T17:57:27Z","abstract_excerpt":"We address the task of indoor scene generation by generating a sequence of objects, along with their locations and orientations conditioned on a room layout. Large-scale indoor scene datasets allow us to extract patterns from user-designed indoor scenes, and generate new scenes based on these patterns. Existing methods rely on the 2D or 3D appearance of these scenes in addition to object positions, and make assumptions about the possible relations between objects. In contrast, we do not use any appearance information, and implicitly learn object relations using the self-attention mechanism of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.09793","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/2012.09793/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":"2026-07-05T02:28:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ffH6XTb8avcGio1tdSjY80sgc6pvM2QbF7FKbjuBNSMDCydyLI8rGeZS1ec4V8Ntr2hij+4Lsghy0skX5dHnDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:08:38.907615Z"},"content_sha256":"545adaf08a8c7ea1541643db778d76d93df03e9c9f6fba8dce78452cab984aee","schema_version":"1.0","event_id":"sha256:545adaf08a8c7ea1541643db778d76d93df03e9c9f6fba8dce78452cab984aee"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MS6ZYHM7LCCJRQCGLHRPGTKXDM/bundle.json","state_url":"https://pith.science/pith/MS6ZYHM7LCCJRQCGLHRPGTKXDM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MS6ZYHM7LCCJRQCGLHRPGTKXDM/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":"2026-08-05T02:08:38Z","links":{"resolver":"https://pith.science/pith/MS6ZYHM7LCCJRQCGLHRPGTKXDM","bundle":"https://pith.science/pith/MS6ZYHM7LCCJRQCGLHRPGTKXDM/bundle.json","state":"https://pith.science/pith/MS6ZYHM7LCCJRQCGLHRPGTKXDM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MS6ZYHM7LCCJRQCGLHRPGTKXDM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:MS6ZYHM7LCCJRQCGLHRPGTKXDM","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":"96006126a88ca5c42d7e9335859b06c8a95d387754835224d34fba093922858f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-12-17T17:57:27Z","title_canon_sha256":"e9d3f380a731b6719dabc819d6aa3b3bf83a615590d39c4aeb7f50cd1e84de77"},"schema_version":"1.0","source":{"id":"2012.09793","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.09793","created_at":"2026-07-05T02:28:33Z"},{"alias_kind":"arxiv_version","alias_value":"2012.09793v2","created_at":"2026-07-05T02:28:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.09793","created_at":"2026-07-05T02:28:33Z"},{"alias_kind":"pith_short_12","alias_value":"MS6ZYHM7LCCJ","created_at":"2026-07-05T02:28:33Z"},{"alias_kind":"pith_short_16","alias_value":"MS6ZYHM7LCCJRQCG","created_at":"2026-07-05T02:28:33Z"},{"alias_kind":"pith_short_8","alias_value":"MS6ZYHM7","created_at":"2026-07-05T02:28:33Z"}],"graph_snapshots":[{"event_id":"sha256:545adaf08a8c7ea1541643db778d76d93df03e9c9f6fba8dce78452cab984aee","target":"graph","created_at":"2026-07-05T02:28:33Z","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/2012.09793/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We address the task of indoor scene generation by generating a sequence of objects, along with their locations and orientations conditioned on a room layout. Large-scale indoor scene datasets allow us to extract patterns from user-designed indoor scenes, and generate new scenes based on these patterns. Existing methods rely on the 2D or 3D appearance of these scenes in addition to object positions, and make assumptions about the possible relations between objects. In contrast, we do not use any appearance information, and implicitly learn object relations using the self-attention mechanism of ","authors_text":"Chandan Yeshwanth, Matthias Nie{\\ss}ner, Xinpeng Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-12-17T17:57:27Z","title":"SceneFormer: Indoor Scene Generation with Transformers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.09793","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":"sha256:3c13401a500a48f55bb183d54beb49aad66e8823502920abba8c36066a7e580b","target":"record","created_at":"2026-07-05T02:28:33Z","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":"96006126a88ca5c42d7e9335859b06c8a95d387754835224d34fba093922858f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-12-17T17:57:27Z","title_canon_sha256":"e9d3f380a731b6719dabc819d6aa3b3bf83a615590d39c4aeb7f50cd1e84de77"},"schema_version":"1.0","source":{"id":"2012.09793","kind":"arxiv","version":2}},"canonical_sha256":"64bd9c1d9f588498c04659e2f34d571b04be37db777a493ce109267d9e0c2e32","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"64bd9c1d9f588498c04659e2f34d571b04be37db777a493ce109267d9e0c2e32","first_computed_at":"2026-07-05T02:28:33.548711Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:28:33.548711Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TgDSnOrnHAb/mZmAhGFWjPuwqGLTxNstUT0+XkjqEwbcaFYhpRtjRunE4s0eoOgF/m66K9+kVCmrZ1daxAUpCA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:28:33.549180Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.09793","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3c13401a500a48f55bb183d54beb49aad66e8823502920abba8c36066a7e580b","sha256:545adaf08a8c7ea1541643db778d76d93df03e9c9f6fba8dce78452cab984aee"],"state_sha256":"b5e3fda27586292136411ff6ffda37a98b70a83d4dd09c56c96dd5cb73096086"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NWWHL2uYlZ4RXyJLyLf6e0M94aabS5CUO//5SU58pHGWK51Q7PU09nR9qTRgZrqxyzHTVmSE/ikDeZ3g9mfGAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T02:08:38.912461Z","bundle_sha256":"36732f8b78b17fa4c00097d9caefb0c499144ede707f9256adff8985ffb1d604"}}