{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:7M33W4SZDQIHFC7L7UJ2UJYM54","short_pith_number":"pith:7M33W4SZ","canonical_record":{"source":{"id":"1801.03252","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-10T07:16:46Z","cross_cats_sorted":[],"title_canon_sha256":"549d2887481f202cabfcbec5823b8bdd92a6c04e334d4e6b29946da28b3be29f","abstract_canon_sha256":"62731fed96d52acc3066a2c65cbdd1f40cc7c2cef1d176b8dbd58bf873b1caec"},"schema_version":"1.0"},"canonical_sha256":"fb37bb72591c10728bebfd13aa270cef3202a5a32d574469dfe0d420f054ce06","source":{"kind":"arxiv","id":"1801.03252","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.03252","created_at":"2026-05-18T00:26:17Z"},{"alias_kind":"arxiv_version","alias_value":"1801.03252v1","created_at":"2026-05-18T00:26:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.03252","created_at":"2026-05-18T00:26:17Z"},{"alias_kind":"pith_short_12","alias_value":"7M33W4SZDQIH","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"7M33W4SZDQIHFC7L","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"7M33W4SZ","created_at":"2026-05-18T12:32:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:7M33W4SZDQIHFC7L7UJ2UJYM54","target":"record","payload":{"canonical_record":{"source":{"id":"1801.03252","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-10T07:16:46Z","cross_cats_sorted":[],"title_canon_sha256":"549d2887481f202cabfcbec5823b8bdd92a6c04e334d4e6b29946da28b3be29f","abstract_canon_sha256":"62731fed96d52acc3066a2c65cbdd1f40cc7c2cef1d176b8dbd58bf873b1caec"},"schema_version":"1.0"},"canonical_sha256":"fb37bb72591c10728bebfd13aa270cef3202a5a32d574469dfe0d420f054ce06","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:26:17.615716Z","signature_b64":"2AwRZVUoPK9cr2/aYUa3jC41r78jCe/oZYppgx/92uDHS5GU/MdX3x8r2JAQNCwlKFWu2dOfxOsEKmAwIv1oDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fb37bb72591c10728bebfd13aa270cef3202a5a32d574469dfe0d420f054ce06","last_reissued_at":"2026-05-18T00:26:17.615053Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:26:17.615053Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1801.03252","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":"2026-05-18T00:26:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZxEDXHh9Nx4W5wuW5z1eGqDEr0plNBI4ELQTB5uYBZRDvJm6zOeNkzyZcKo6P+8pzEOV6p+0sLVyrp/GIoL6Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T13:07:29.659238Z"},"content_sha256":"71d66321f9d9322c4cf8851c0d1706249ced78cd714cae81556539ff8949cedd","schema_version":"1.0","event_id":"sha256:71d66321f9d9322c4cf8851c0d1706249ced78cd714cae81556539ff8949cedd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:7M33W4SZDQIHFC7L7UJ2UJYM54","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Instance Map based Image Synthesis with a Denoising Generative Adversarial Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bing Zheng, Chao Wang, Haiyong Zheng, Zhibin Yu, Ziqiang Zheng","submitted_at":"2018-01-10T07:16:46Z","abstract_excerpt":"Semantic layouts based Image synthesizing, which has benefited from the success of Generative Adversarial Network (GAN), has drawn much attention in these days. How to enhance the synthesis image equality while keeping the stochasticity of the GAN is still a challenge. We propose a novel denoising framework to handle this problem. The overlapped objects generation is another challenging task when synthesizing images from a semantic layout to a realistic RGB photo. To overcome this deficiency, we include a one-hot semantic label map to force the generator paying more attention on the overlapped"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.03252","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":""},"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":"2026-05-18T00:26:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ut9VMFk2gIgjihghyLctlPMSM7fEll2sRR0Wz8EeQbuInbNSmbyuCE64/HbLDOFQ/q7gT1S1b3Ll7S697S12BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T13:07:29.659932Z"},"content_sha256":"7c1db6e9314df60c0a239030ced6e2a5cfdd0de7bba9162bd69f34766b0f18bd","schema_version":"1.0","event_id":"sha256:7c1db6e9314df60c0a239030ced6e2a5cfdd0de7bba9162bd69f34766b0f18bd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7M33W4SZDQIHFC7L7UJ2UJYM54/bundle.json","state_url":"https://pith.science/pith/7M33W4SZDQIHFC7L7UJ2UJYM54/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7M33W4SZDQIHFC7L7UJ2UJYM54/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":"2026-05-31T13:07:29Z","links":{"resolver":"https://pith.science/pith/7M33W4SZDQIHFC7L7UJ2UJYM54","bundle":"https://pith.science/pith/7M33W4SZDQIHFC7L7UJ2UJYM54/bundle.json","state":"https://pith.science/pith/7M33W4SZDQIHFC7L7UJ2UJYM54/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7M33W4SZDQIHFC7L7UJ2UJYM54/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:7M33W4SZDQIHFC7L7UJ2UJYM54","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":"62731fed96d52acc3066a2c65cbdd1f40cc7c2cef1d176b8dbd58bf873b1caec","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-10T07:16:46Z","title_canon_sha256":"549d2887481f202cabfcbec5823b8bdd92a6c04e334d4e6b29946da28b3be29f"},"schema_version":"1.0","source":{"id":"1801.03252","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.03252","created_at":"2026-05-18T00:26:17Z"},{"alias_kind":"arxiv_version","alias_value":"1801.03252v1","created_at":"2026-05-18T00:26:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.03252","created_at":"2026-05-18T00:26:17Z"},{"alias_kind":"pith_short_12","alias_value":"7M33W4SZDQIH","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"7M33W4SZDQIHFC7L","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"7M33W4SZ","created_at":"2026-05-18T12:32:11Z"}],"graph_snapshots":[{"event_id":"sha256:7c1db6e9314df60c0a239030ced6e2a5cfdd0de7bba9162bd69f34766b0f18bd","target":"graph","created_at":"2026-05-18T00:26:17Z","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":"Semantic layouts based Image synthesizing, which has benefited from the success of Generative Adversarial Network (GAN), has drawn much attention in these days. How to enhance the synthesis image equality while keeping the stochasticity of the GAN is still a challenge. We propose a novel denoising framework to handle this problem. The overlapped objects generation is another challenging task when synthesizing images from a semantic layout to a realistic RGB photo. To overcome this deficiency, we include a one-hot semantic label map to force the generator paying more attention on the overlapped","authors_text":"Bing Zheng, Chao Wang, Haiyong Zheng, Zhibin Yu, Ziqiang Zheng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-10T07:16:46Z","title":"Instance Map based Image Synthesis with a Denoising Generative Adversarial Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.03252","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":"sha256:71d66321f9d9322c4cf8851c0d1706249ced78cd714cae81556539ff8949cedd","target":"record","created_at":"2026-05-18T00:26:17Z","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":"62731fed96d52acc3066a2c65cbdd1f40cc7c2cef1d176b8dbd58bf873b1caec","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-10T07:16:46Z","title_canon_sha256":"549d2887481f202cabfcbec5823b8bdd92a6c04e334d4e6b29946da28b3be29f"},"schema_version":"1.0","source":{"id":"1801.03252","kind":"arxiv","version":1}},"canonical_sha256":"fb37bb72591c10728bebfd13aa270cef3202a5a32d574469dfe0d420f054ce06","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fb37bb72591c10728bebfd13aa270cef3202a5a32d574469dfe0d420f054ce06","first_computed_at":"2026-05-18T00:26:17.615053Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:26:17.615053Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2AwRZVUoPK9cr2/aYUa3jC41r78jCe/oZYppgx/92uDHS5GU/MdX3x8r2JAQNCwlKFWu2dOfxOsEKmAwIv1oDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:26:17.615716Z","signed_message":"canonical_sha256_bytes"},"source_id":"1801.03252","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:71d66321f9d9322c4cf8851c0d1706249ced78cd714cae81556539ff8949cedd","sha256:7c1db6e9314df60c0a239030ced6e2a5cfdd0de7bba9162bd69f34766b0f18bd"],"state_sha256":"79b4ef1efc29ddb1b97fdfc7ad3213573491c8c088279d984b2464b7fdab5b03"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SvudoJrzkWgsEMe9nDc3rUo/pYVGkT0Of+vpzIkqj7wJkC2T49LxSH04YzpNdDhfjoZ9UfcsVmbuE2bXoDRSDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T13:07:29.663738Z","bundle_sha256":"f068cd74d5cc0b4286d58567cf7aa5e76871afed2d9d1ed801b83a413fe0cea3"}}