{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:2X3C5BZRZ6NFFUBPI7AWBGXTVQ","short_pith_number":"pith:2X3C5BZR","canonical_record":{"source":{"id":"1711.08174","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-22T08:36:39Z","cross_cats_sorted":[],"title_canon_sha256":"90d83b0cfa6666c5797f8a843db3cbe29642e21a57adf89f506439bdc889d62a","abstract_canon_sha256":"261e4abfc513a67bcf4492a331afd4aba61595722910b01dd1fc83f548fc29b5"},"schema_version":"1.0"},"canonical_sha256":"d5f62e8731cf9a52d02f47c1609af3ac0e14455c9744ba55b3e3b8e5738e2a99","source":{"kind":"arxiv","id":"1711.08174","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.08174","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"arxiv_version","alias_value":"1711.08174v2","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.08174","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"pith_short_12","alias_value":"2X3C5BZRZ6NF","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"2X3C5BZRZ6NFFUBP","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"2X3C5BZR","created_at":"2026-05-18T12:30:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:2X3C5BZRZ6NFFUBPI7AWBGXTVQ","target":"record","payload":{"canonical_record":{"source":{"id":"1711.08174","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-22T08:36:39Z","cross_cats_sorted":[],"title_canon_sha256":"90d83b0cfa6666c5797f8a843db3cbe29642e21a57adf89f506439bdc889d62a","abstract_canon_sha256":"261e4abfc513a67bcf4492a331afd4aba61595722910b01dd1fc83f548fc29b5"},"schema_version":"1.0"},"canonical_sha256":"d5f62e8731cf9a52d02f47c1609af3ac0e14455c9744ba55b3e3b8e5738e2a99","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:25.510770Z","signature_b64":"ZB4tnMBjkaKNiSgCqG+1mPjIzMLylyVFIy4SfPUZfpdkBt9o4Z6WXEMyTdjZqW354pvx2t99dTArCEhf01aiCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d5f62e8731cf9a52d02f47c1609af3ac0e14455c9744ba55b3e3b8e5738e2a99","last_reissued_at":"2026-05-18T00:18:25.510191Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:25.510191Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.08174","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":"2026-05-18T00:18:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P31yW+OAVD5m7PJxMVmR2rRFptwmCxbJtD+tcWg8jgoXBHyFSdMCPwxXbNQrKgvOeP6/sMELqmCfJCmOb3puBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T05:22:11.177994Z"},"content_sha256":"c4fc6ce5cd58b8f7b1f8665ac4bb95ecc093ce0e7e6b2b5e08f071349540b37a","schema_version":"1.0","event_id":"sha256:c4fc6ce5cd58b8f7b1f8665ac4bb95ecc093ce0e7e6b2b5e08f071349540b37a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:2X3C5BZRZ6NFFUBPI7AWBGXTVQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ali Diba, Luc Van Gool, Rainer Stiefelhagen, Vivek Sharma","submitted_at":"2017-11-22T08:36:39Z","abstract_excerpt":"The deep generative adversarial networks (GAN) recently have been shown to be promising for different computer vision applications, like image edit- ing, synthesizing high resolution images, generating videos, etc. These networks and the corresponding learning scheme can handle various visual space map- pings. We approach GANs with a novel training method and learning objective, to discover multiple object instances for three cases: 1) synthesizing a picture of a specific object within a cluttered scene; 2) localizing different categories in images for weakly supervised object detection; and 3"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.08174","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":""},"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":"2026-05-18T00:18:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jNHyspLs4rkQ8M8V5NpwrSw7aV2A9cT/zDDeozFdXfKQRucQZhwVRpOYN0HmZnNRGM9BNwFY725ZycHptmCvAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T05:22:11.178347Z"},"content_sha256":"e3884dd90a6a14bf7fd829399d69c968b5a51ed93ca82ffb95b404933a61cd52","schema_version":"1.0","event_id":"sha256:e3884dd90a6a14bf7fd829399d69c968b5a51ed93ca82ffb95b404933a61cd52"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2X3C5BZRZ6NFFUBPI7AWBGXTVQ/bundle.json","state_url":"https://pith.science/pith/2X3C5BZRZ6NFFUBPI7AWBGXTVQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2X3C5BZRZ6NFFUBPI7AWBGXTVQ/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":"2026-06-01T05:22:11Z","links":{"resolver":"https://pith.science/pith/2X3C5BZRZ6NFFUBPI7AWBGXTVQ","bundle":"https://pith.science/pith/2X3C5BZRZ6NFFUBPI7AWBGXTVQ/bundle.json","state":"https://pith.science/pith/2X3C5BZRZ6NFFUBPI7AWBGXTVQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2X3C5BZRZ6NFFUBPI7AWBGXTVQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:2X3C5BZRZ6NFFUBPI7AWBGXTVQ","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":"261e4abfc513a67bcf4492a331afd4aba61595722910b01dd1fc83f548fc29b5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-22T08:36:39Z","title_canon_sha256":"90d83b0cfa6666c5797f8a843db3cbe29642e21a57adf89f506439bdc889d62a"},"schema_version":"1.0","source":{"id":"1711.08174","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.08174","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"arxiv_version","alias_value":"1711.08174v2","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.08174","created_at":"2026-05-18T00:18:25Z"},{"alias_kind":"pith_short_12","alias_value":"2X3C5BZRZ6NF","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"2X3C5BZRZ6NFFUBP","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"2X3C5BZR","created_at":"2026-05-18T12:30:55Z"}],"graph_snapshots":[{"event_id":"sha256:e3884dd90a6a14bf7fd829399d69c968b5a51ed93ca82ffb95b404933a61cd52","target":"graph","created_at":"2026-05-18T00:18:25Z","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":"The deep generative adversarial networks (GAN) recently have been shown to be promising for different computer vision applications, like image edit- ing, synthesizing high resolution images, generating videos, etc. These networks and the corresponding learning scheme can handle various visual space map- pings. We approach GANs with a novel training method and learning objective, to discover multiple object instances for three cases: 1) synthesizing a picture of a specific object within a cluttered scene; 2) localizing different categories in images for weakly supervised object detection; and 3","authors_text":"Ali Diba, Luc Van Gool, Rainer Stiefelhagen, Vivek Sharma","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-22T08:36:39Z","title":"Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.08174","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:c4fc6ce5cd58b8f7b1f8665ac4bb95ecc093ce0e7e6b2b5e08f071349540b37a","target":"record","created_at":"2026-05-18T00:18:25Z","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":"261e4abfc513a67bcf4492a331afd4aba61595722910b01dd1fc83f548fc29b5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-22T08:36:39Z","title_canon_sha256":"90d83b0cfa6666c5797f8a843db3cbe29642e21a57adf89f506439bdc889d62a"},"schema_version":"1.0","source":{"id":"1711.08174","kind":"arxiv","version":2}},"canonical_sha256":"d5f62e8731cf9a52d02f47c1609af3ac0e14455c9744ba55b3e3b8e5738e2a99","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d5f62e8731cf9a52d02f47c1609af3ac0e14455c9744ba55b3e3b8e5738e2a99","first_computed_at":"2026-05-18T00:18:25.510191Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:18:25.510191Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZB4tnMBjkaKNiSgCqG+1mPjIzMLylyVFIy4SfPUZfpdkBt9o4Z6WXEMyTdjZqW354pvx2t99dTArCEhf01aiCg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:18:25.510770Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.08174","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4fc6ce5cd58b8f7b1f8665ac4bb95ecc093ce0e7e6b2b5e08f071349540b37a","sha256:e3884dd90a6a14bf7fd829399d69c968b5a51ed93ca82ffb95b404933a61cd52"],"state_sha256":"e3913a179e88b1e302707315d15c7e649b17ef37710a09e8635963b0e0a4cc17"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ymqDjfyf6Ik2a7owGYSdsnJn6QKWSlDU1+jvT6CQTUi0jpXw0YBtNHziV8GaPnOI+VWgW9wsowz/mLJCKZXcAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T05:22:11.180701Z","bundle_sha256":"66508b253e64a8b857c245ffff9a45581905075bfa3293a8c47379b3ecf12599"}}