{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:INK5G5XPSI6NOHPHP4JNNZAQLK","short_pith_number":"pith:INK5G5XP","canonical_record":{"source":{"id":"1703.08448","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-03-24T15:05:38Z","cross_cats_sorted":[],"title_canon_sha256":"d02b6b07927d2b0312b7f7f32bc319c73ffa24ab06874d62148d122dfac56050","abstract_canon_sha256":"f4b953f8f7eac97e361f74bb117a038b8392c4e575b5f9c9443469b0ceadaa8c"},"schema_version":"1.0"},"canonical_sha256":"4355d376ef923cd71de77f12d6e4105aae755c886af620b7394a211ba843bb1a","source":{"kind":"arxiv","id":"1703.08448","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.08448","created_at":"2026-05-18T00:14:57Z"},{"alias_kind":"arxiv_version","alias_value":"1703.08448v3","created_at":"2026-05-18T00:14:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.08448","created_at":"2026-05-18T00:14:57Z"},{"alias_kind":"pith_short_12","alias_value":"INK5G5XPSI6N","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"INK5G5XPSI6NOHPH","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"INK5G5XP","created_at":"2026-05-18T12:31:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:INK5G5XPSI6NOHPHP4JNNZAQLK","target":"record","payload":{"canonical_record":{"source":{"id":"1703.08448","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-03-24T15:05:38Z","cross_cats_sorted":[],"title_canon_sha256":"d02b6b07927d2b0312b7f7f32bc319c73ffa24ab06874d62148d122dfac56050","abstract_canon_sha256":"f4b953f8f7eac97e361f74bb117a038b8392c4e575b5f9c9443469b0ceadaa8c"},"schema_version":"1.0"},"canonical_sha256":"4355d376ef923cd71de77f12d6e4105aae755c886af620b7394a211ba843bb1a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:57.115150Z","signature_b64":"lhBI7ibbogNd3Fv7Ytv+zdWZHAoG/vQUJFGlR57lbbz8Mo+hlpcSJgRGB2zcLll6iMtN/hfLqPjbYWIY9JUrCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4355d376ef923cd71de77f12d6e4105aae755c886af620b7394a211ba843bb1a","last_reissued_at":"2026-05-18T00:14:57.114474Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:57.114474Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.08448","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":"2026-05-18T00:14:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aXYkDE91Z3ZSsWwv/rjvL5cismoaXmJdlZPpcuxp2ib5WnbOHRdZWTjICPxe2njDarvBfoBAADX++b6jupo+AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T03:58:50.018995Z"},"content_sha256":"a706b3552f841d9b07a1cdfbc1c534d0e59bfb3fd80828f646a78297a691479c","schema_version":"1.0","event_id":"sha256:a706b3552f841d9b07a1cdfbc1c534d0e59bfb3fd80828f646a78297a691479c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:INK5G5XPSI6NOHPHP4JNNZAQLK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jiashi Feng, Ming-Ming Cheng, Shuicheng Yan, Xiaodan Liang, Yao Zhao, Yunchao Wei","submitted_at":"2017-03-24T15:05:38Z","abstract_excerpt":"We investigate a principle way to progressively mine discriminative object regions using classification networks to address the weakly-supervised semantic segmentation problems. Classification networks are only responsive to small and sparse discriminative regions from the object of interest, which deviates from the requirement of the segmentation task that needs to localize dense, interior and integral regions for pixel-wise inference. To mitigate this gap, we propose a new adversarial erasing approach for localizing and expanding object regions progressively. Starting with a single small obj"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.08448","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":""},"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":"2026-05-18T00:14:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wnyvB32m+9RfTV/y/JWs/wZMDi6Tcc+8HlwAbQOgfwPMiQjEcelUR1esGYW//DY8306jIbfLpQju6uGkPfhwCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T03:58:50.019612Z"},"content_sha256":"708468305b1bb2c8b24fe8825022aa568e0857eca243f00dbc86204722abda26","schema_version":"1.0","event_id":"sha256:708468305b1bb2c8b24fe8825022aa568e0857eca243f00dbc86204722abda26"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/INK5G5XPSI6NOHPHP4JNNZAQLK/bundle.json","state_url":"https://pith.science/pith/INK5G5XPSI6NOHPHP4JNNZAQLK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/INK5G5XPSI6NOHPHP4JNNZAQLK/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":"2026-06-05T03:58:50Z","links":{"resolver":"https://pith.science/pith/INK5G5XPSI6NOHPHP4JNNZAQLK","bundle":"https://pith.science/pith/INK5G5XPSI6NOHPHP4JNNZAQLK/bundle.json","state":"https://pith.science/pith/INK5G5XPSI6NOHPHP4JNNZAQLK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/INK5G5XPSI6NOHPHP4JNNZAQLK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:INK5G5XPSI6NOHPHP4JNNZAQLK","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":"f4b953f8f7eac97e361f74bb117a038b8392c4e575b5f9c9443469b0ceadaa8c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-03-24T15:05:38Z","title_canon_sha256":"d02b6b07927d2b0312b7f7f32bc319c73ffa24ab06874d62148d122dfac56050"},"schema_version":"1.0","source":{"id":"1703.08448","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.08448","created_at":"2026-05-18T00:14:57Z"},{"alias_kind":"arxiv_version","alias_value":"1703.08448v3","created_at":"2026-05-18T00:14:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.08448","created_at":"2026-05-18T00:14:57Z"},{"alias_kind":"pith_short_12","alias_value":"INK5G5XPSI6N","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"INK5G5XPSI6NOHPH","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"INK5G5XP","created_at":"2026-05-18T12:31:21Z"}],"graph_snapshots":[{"event_id":"sha256:708468305b1bb2c8b24fe8825022aa568e0857eca243f00dbc86204722abda26","target":"graph","created_at":"2026-05-18T00:14:57Z","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":"We investigate a principle way to progressively mine discriminative object regions using classification networks to address the weakly-supervised semantic segmentation problems. Classification networks are only responsive to small and sparse discriminative regions from the object of interest, which deviates from the requirement of the segmentation task that needs to localize dense, interior and integral regions for pixel-wise inference. To mitigate this gap, we propose a new adversarial erasing approach for localizing and expanding object regions progressively. Starting with a single small obj","authors_text":"Jiashi Feng, Ming-Ming Cheng, Shuicheng Yan, Xiaodan Liang, Yao Zhao, Yunchao Wei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-03-24T15:05:38Z","title":"Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.08448","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:a706b3552f841d9b07a1cdfbc1c534d0e59bfb3fd80828f646a78297a691479c","target":"record","created_at":"2026-05-18T00:14:57Z","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":"f4b953f8f7eac97e361f74bb117a038b8392c4e575b5f9c9443469b0ceadaa8c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-03-24T15:05:38Z","title_canon_sha256":"d02b6b07927d2b0312b7f7f32bc319c73ffa24ab06874d62148d122dfac56050"},"schema_version":"1.0","source":{"id":"1703.08448","kind":"arxiv","version":3}},"canonical_sha256":"4355d376ef923cd71de77f12d6e4105aae755c886af620b7394a211ba843bb1a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4355d376ef923cd71de77f12d6e4105aae755c886af620b7394a211ba843bb1a","first_computed_at":"2026-05-18T00:14:57.114474Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:57.114474Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lhBI7ibbogNd3Fv7Ytv+zdWZHAoG/vQUJFGlR57lbbz8Mo+hlpcSJgRGB2zcLll6iMtN/hfLqPjbYWIY9JUrCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:57.115150Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.08448","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a706b3552f841d9b07a1cdfbc1c534d0e59bfb3fd80828f646a78297a691479c","sha256:708468305b1bb2c8b24fe8825022aa568e0857eca243f00dbc86204722abda26"],"state_sha256":"8bbb8ce5920a7c6d037d5cd9b6743f599566c1309f304249d89f3e604244e8c4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fJ7R80oz9SSoJmvvOzlB5BtAz2oqhc2BmmXywuY8UfHesInROK6tCrkngF98A2+BknJ0ec48TU4oMoFqCNJlAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T03:58:50.022964Z","bundle_sha256":"5cfbe8c1a95c82505732f343dd119ca74a9e9e97d9d42923e79d9b35bda28d58"}}