{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:74OHZ4427EBEFXEARPEV7VBK27","short_pith_number":"pith:74OHZ442","canonical_record":{"source":{"id":"2002.03370","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-02-09T14:21:08Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"4211aab5f5e90655effbc3dd3f654ce0a60342b9e70232eae6175f61ae0edd30","abstract_canon_sha256":"5bc7d9a8d769b77aef1762bff5470672611fd5353111f55cef1382932037a480"},"schema_version":"1.0"},"canonical_sha256":"ff1c7cf39af90242dc808bc95fd42ad7ee73f84797c66cc8b1f5f436739a3972","source":{"kind":"arxiv","id":"2002.03370","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.03370","created_at":"2026-07-05T01:05:11Z"},{"alias_kind":"arxiv_version","alias_value":"2002.03370v3","created_at":"2026-07-05T01:05:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.03370","created_at":"2026-07-05T01:05:11Z"},{"alias_kind":"pith_short_12","alias_value":"74OHZ4427EBE","created_at":"2026-07-05T01:05:11Z"},{"alias_kind":"pith_short_16","alias_value":"74OHZ4427EBEFXEA","created_at":"2026-07-05T01:05:11Z"},{"alias_kind":"pith_short_8","alias_value":"74OHZ442","created_at":"2026-07-05T01:05:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:74OHZ4427EBEFXEARPEV7VBK27","target":"record","payload":{"canonical_record":{"source":{"id":"2002.03370","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-02-09T14:21:08Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"4211aab5f5e90655effbc3dd3f654ce0a60342b9e70232eae6175f61ae0edd30","abstract_canon_sha256":"5bc7d9a8d769b77aef1762bff5470672611fd5353111f55cef1382932037a480"},"schema_version":"1.0"},"canonical_sha256":"ff1c7cf39af90242dc808bc95fd42ad7ee73f84797c66cc8b1f5f436739a3972","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:05:11.674482Z","signature_b64":"C3BFsyak/W7I8XBZMkRMG/F4nquzVsH40Yfo6CsEXXPcuFBpP0/Iw6xWJmsMqlulqxBpA6/UFZMKfpIQQfMyDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ff1c7cf39af90242dc808bc95fd42ad7ee73f84797c66cc8b1f5f436739a3972","last_reissued_at":"2026-07-05T01:05:11.674016Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:05:11.674016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.03370","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:05:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7PJsHR188IWIWgAlsWV6qdUeuhfRLZ/t+3RecLKv/jRh8/mBpggXvHDKWZPue3Hi01Zi5zkuljr8RdKQQktlDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:00:55.136857Z"},"content_sha256":"2b465c221569113a47ca15c383e765d63414208bd9544295278736b8b0267626","schema_version":"1.0","event_id":"sha256:2b465c221569113a47ca15c383e765d63414208bd9544295278736b8b0267626"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:74OHZ4427EBEFXEARPEV7VBK27","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Unified End-to-End Framework for Efficient Deep Image Compression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Dong Xu, Guo Lu, Jiaheng Liu, Zhihao Hu","submitted_at":"2020-02-09T14:21:08Z","abstract_excerpt":"Image compression is a widely used technique to reduce the spatial redundancy in images. Recently, learning based image compression has achieved significant progress by using the powerful representation ability from neural networks. However, the current state-of-the-art learning based image compression methods suffer from the huge computational cost, which limits their capacity for practical applications. In this paper, we propose a unified framework called Efficient Deep Image Compression (EDIC) based on three new technologies, including a channel attention module, a Gaussian mixture model an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.03370","kind":"arxiv","version":3},"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/2002.03370/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":"2026-07-05T01:05:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yIAC+CPd6dFERgHI+dULPeBczRAb819bWAOhxz+eFJpsaMhgwo8uXigyugylBFrYDlexmUZbWf+N3QR21R9eCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:00:55.137355Z"},"content_sha256":"340fa75eb90bccc7e38ba715929124fae9e8283055825002a5bf26bed3c38f65","schema_version":"1.0","event_id":"sha256:340fa75eb90bccc7e38ba715929124fae9e8283055825002a5bf26bed3c38f65"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/74OHZ4427EBEFXEARPEV7VBK27/bundle.json","state_url":"https://pith.science/pith/74OHZ4427EBEFXEARPEV7VBK27/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/74OHZ4427EBEFXEARPEV7VBK27/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":"2026-08-09T15:00:55Z","links":{"resolver":"https://pith.science/pith/74OHZ4427EBEFXEARPEV7VBK27","bundle":"https://pith.science/pith/74OHZ4427EBEFXEARPEV7VBK27/bundle.json","state":"https://pith.science/pith/74OHZ4427EBEFXEARPEV7VBK27/state.json","well_known_bundle":"https://pith.science/.well-known/pith/74OHZ4427EBEFXEARPEV7VBK27/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:74OHZ4427EBEFXEARPEV7VBK27","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":"5bc7d9a8d769b77aef1762bff5470672611fd5353111f55cef1382932037a480","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-02-09T14:21:08Z","title_canon_sha256":"4211aab5f5e90655effbc3dd3f654ce0a60342b9e70232eae6175f61ae0edd30"},"schema_version":"1.0","source":{"id":"2002.03370","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.03370","created_at":"2026-07-05T01:05:11Z"},{"alias_kind":"arxiv_version","alias_value":"2002.03370v3","created_at":"2026-07-05T01:05:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.03370","created_at":"2026-07-05T01:05:11Z"},{"alias_kind":"pith_short_12","alias_value":"74OHZ4427EBE","created_at":"2026-07-05T01:05:11Z"},{"alias_kind":"pith_short_16","alias_value":"74OHZ4427EBEFXEA","created_at":"2026-07-05T01:05:11Z"},{"alias_kind":"pith_short_8","alias_value":"74OHZ442","created_at":"2026-07-05T01:05:11Z"}],"graph_snapshots":[{"event_id":"sha256:340fa75eb90bccc7e38ba715929124fae9e8283055825002a5bf26bed3c38f65","target":"graph","created_at":"2026-07-05T01:05:11Z","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/2002.03370/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Image compression is a widely used technique to reduce the spatial redundancy in images. Recently, learning based image compression has achieved significant progress by using the powerful representation ability from neural networks. However, the current state-of-the-art learning based image compression methods suffer from the huge computational cost, which limits their capacity for practical applications. In this paper, we propose a unified framework called Efficient Deep Image Compression (EDIC) based on three new technologies, including a channel attention module, a Gaussian mixture model an","authors_text":"Dong Xu, Guo Lu, Jiaheng Liu, Zhihao Hu","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-02-09T14:21:08Z","title":"A Unified End-to-End Framework for Efficient Deep Image Compression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.03370","kind":"arxiv","version":3},"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":"sha256:2b465c221569113a47ca15c383e765d63414208bd9544295278736b8b0267626","target":"record","created_at":"2026-07-05T01:05:11Z","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":"5bc7d9a8d769b77aef1762bff5470672611fd5353111f55cef1382932037a480","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-02-09T14:21:08Z","title_canon_sha256":"4211aab5f5e90655effbc3dd3f654ce0a60342b9e70232eae6175f61ae0edd30"},"schema_version":"1.0","source":{"id":"2002.03370","kind":"arxiv","version":3}},"canonical_sha256":"ff1c7cf39af90242dc808bc95fd42ad7ee73f84797c66cc8b1f5f436739a3972","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff1c7cf39af90242dc808bc95fd42ad7ee73f84797c66cc8b1f5f436739a3972","first_computed_at":"2026-07-05T01:05:11.674016Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:05:11.674016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"C3BFsyak/W7I8XBZMkRMG/F4nquzVsH40Yfo6CsEXXPcuFBpP0/Iw6xWJmsMqlulqxBpA6/UFZMKfpIQQfMyDA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:05:11.674482Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.03370","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2b465c221569113a47ca15c383e765d63414208bd9544295278736b8b0267626","sha256:340fa75eb90bccc7e38ba715929124fae9e8283055825002a5bf26bed3c38f65"],"state_sha256":"c43da68c58b35af4924cb92649cebb838f608a5309a95590fea7014db332f88c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qUBpmA28nP/R71dArai+Y/IZUzCa7LWu6TBkp0ZLfFEzWAsbGP+z5jitUmFUB7BCZJNb1BkTUYBHLMyMv/ogAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T15:00:55.142462Z","bundle_sha256":"eebefa5ef36b6c74828c74fcdd8bf0872ad969a8681dbccf6a34441a8bf62ab7"}}