{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:DSABA3KSB3QOLIGGAHKZLMA5DN","short_pith_number":"pith:DSABA3KS","canonical_record":{"source":{"id":"2211.12425","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T17:31:43Z","cross_cats_sorted":[],"title_canon_sha256":"d573f958357a3ff77c15e40c6a27d0704e0c3969f2dad245838005ce9f56b06a","abstract_canon_sha256":"ea3554cfa718116621d0bbbcf55c97311e9fae457d4f93ff532d973fe09b3edf"},"schema_version":"1.0"},"canonical_sha256":"1c80106d520ee0e5a0c601d595b01d1b67ef6d6033bc75a8da35dae3ac79c94b","source":{"kind":"arxiv","id":"2211.12425","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.12425","created_at":"2026-07-05T05:54:33Z"},{"alias_kind":"arxiv_version","alias_value":"2211.12425v2","created_at":"2026-07-05T05:54:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.12425","created_at":"2026-07-05T05:54:33Z"},{"alias_kind":"pith_short_12","alias_value":"DSABA3KSB3QO","created_at":"2026-07-05T05:54:33Z"},{"alias_kind":"pith_short_16","alias_value":"DSABA3KSB3QOLIGG","created_at":"2026-07-05T05:54:33Z"},{"alias_kind":"pith_short_8","alias_value":"DSABA3KS","created_at":"2026-07-05T05:54:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:DSABA3KSB3QOLIGGAHKZLMA5DN","target":"record","payload":{"canonical_record":{"source":{"id":"2211.12425","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T17:31:43Z","cross_cats_sorted":[],"title_canon_sha256":"d573f958357a3ff77c15e40c6a27d0704e0c3969f2dad245838005ce9f56b06a","abstract_canon_sha256":"ea3554cfa718116621d0bbbcf55c97311e9fae457d4f93ff532d973fe09b3edf"},"schema_version":"1.0"},"canonical_sha256":"1c80106d520ee0e5a0c601d595b01d1b67ef6d6033bc75a8da35dae3ac79c94b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:54:33.655862Z","signature_b64":"WQzD/H/eBTzYCmevfaQwdMfGe+fpsA2VqRRUIzFYzF6spqi+iT13KSJrQ+CQV+Zy8bfukU/Haoe3wmeJU/doBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1c80106d520ee0e5a0c601d595b01d1b67ef6d6033bc75a8da35dae3ac79c94b","last_reissued_at":"2026-07-05T05:54:33.655329Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:54:33.655329Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.12425","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":"2026-07-05T05:54:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eNInqiLCAZ40B5k5+0z000LYb2TbFvjmElDTljs7GByPcDIrYrtOy66kkceu03lacUnjP5irJDz4I2lPk4fEBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T18:13:28.443145Z"},"content_sha256":"dd416558bfca939de3cd138fda33315700d449a57de6ff0c1d6d5fbb66dd3f07","schema_version":"1.0","event_id":"sha256:dd416558bfca939de3cd138fda33315700d449a57de6ff0c1d6d5fbb66dd3f07"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:DSABA3KSB3QOLIGGAHKZLMA5DN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Progressive Learning with Cross-Window Consistency for Semi-Supervised Semantic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bo Dang, Jiayi Ma, Yansheng Li, Yongjun Zhang","submitted_at":"2022-11-22T17:31:43Z","abstract_excerpt":"Semi-supervised semantic segmentation focuses on the exploration of a small amount of labeled data and a large amount of unlabeled data, which is more in line with the demands of real-world image understanding applications. However, it is still hindered by the inability to fully and effectively leverage unlabeled images. In this paper, we reveal that cross-window consistency (CWC) is helpful in comprehensively extracting auxiliary supervision from unlabeled data. Additionally, we propose a novel CWC-driven progressive learning framework to optimize the deep network by mining weak-to-strong con"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.12425","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/2211.12425/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":"2026-07-05T05:54:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sFvgBvegDZgQXL91qy5chEAjftyaz0cWDcMyXfbrbqKIPpgB8VoVDqgFlW9oWm1Y6CUDX2uJvJRg/Z/vm934Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T18:13:28.443535Z"},"content_sha256":"443714eaa0247a367dd5fb4212af6af2ce1f38e3e40387e3b7152abf008d2966","schema_version":"1.0","event_id":"sha256:443714eaa0247a367dd5fb4212af6af2ce1f38e3e40387e3b7152abf008d2966"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DSABA3KSB3QOLIGGAHKZLMA5DN/bundle.json","state_url":"https://pith.science/pith/DSABA3KSB3QOLIGGAHKZLMA5DN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DSABA3KSB3QOLIGGAHKZLMA5DN/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":"2026-07-11T18:13:28Z","links":{"resolver":"https://pith.science/pith/DSABA3KSB3QOLIGGAHKZLMA5DN","bundle":"https://pith.science/pith/DSABA3KSB3QOLIGGAHKZLMA5DN/bundle.json","state":"https://pith.science/pith/DSABA3KSB3QOLIGGAHKZLMA5DN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DSABA3KSB3QOLIGGAHKZLMA5DN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:DSABA3KSB3QOLIGGAHKZLMA5DN","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":"ea3554cfa718116621d0bbbcf55c97311e9fae457d4f93ff532d973fe09b3edf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T17:31:43Z","title_canon_sha256":"d573f958357a3ff77c15e40c6a27d0704e0c3969f2dad245838005ce9f56b06a"},"schema_version":"1.0","source":{"id":"2211.12425","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.12425","created_at":"2026-07-05T05:54:33Z"},{"alias_kind":"arxiv_version","alias_value":"2211.12425v2","created_at":"2026-07-05T05:54:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.12425","created_at":"2026-07-05T05:54:33Z"},{"alias_kind":"pith_short_12","alias_value":"DSABA3KSB3QO","created_at":"2026-07-05T05:54:33Z"},{"alias_kind":"pith_short_16","alias_value":"DSABA3KSB3QOLIGG","created_at":"2026-07-05T05:54:33Z"},{"alias_kind":"pith_short_8","alias_value":"DSABA3KS","created_at":"2026-07-05T05:54:33Z"}],"graph_snapshots":[{"event_id":"sha256:443714eaa0247a367dd5fb4212af6af2ce1f38e3e40387e3b7152abf008d2966","target":"graph","created_at":"2026-07-05T05:54:33Z","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/2211.12425/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semi-supervised semantic segmentation focuses on the exploration of a small amount of labeled data and a large amount of unlabeled data, which is more in line with the demands of real-world image understanding applications. However, it is still hindered by the inability to fully and effectively leverage unlabeled images. In this paper, we reveal that cross-window consistency (CWC) is helpful in comprehensively extracting auxiliary supervision from unlabeled data. Additionally, we propose a novel CWC-driven progressive learning framework to optimize the deep network by mining weak-to-strong con","authors_text":"Bo Dang, Jiayi Ma, Yansheng Li, Yongjun Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T17:31:43Z","title":"Progressive Learning with Cross-Window Consistency for Semi-Supervised Semantic Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.12425","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:dd416558bfca939de3cd138fda33315700d449a57de6ff0c1d6d5fbb66dd3f07","target":"record","created_at":"2026-07-05T05:54:33Z","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":"ea3554cfa718116621d0bbbcf55c97311e9fae457d4f93ff532d973fe09b3edf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T17:31:43Z","title_canon_sha256":"d573f958357a3ff77c15e40c6a27d0704e0c3969f2dad245838005ce9f56b06a"},"schema_version":"1.0","source":{"id":"2211.12425","kind":"arxiv","version":2}},"canonical_sha256":"1c80106d520ee0e5a0c601d595b01d1b67ef6d6033bc75a8da35dae3ac79c94b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1c80106d520ee0e5a0c601d595b01d1b67ef6d6033bc75a8da35dae3ac79c94b","first_computed_at":"2026-07-05T05:54:33.655329Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:54:33.655329Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WQzD/H/eBTzYCmevfaQwdMfGe+fpsA2VqRRUIzFYzF6spqi+iT13KSJrQ+CQV+Zy8bfukU/Haoe3wmeJU/doBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:54:33.655862Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.12425","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dd416558bfca939de3cd138fda33315700d449a57de6ff0c1d6d5fbb66dd3f07","sha256:443714eaa0247a367dd5fb4212af6af2ce1f38e3e40387e3b7152abf008d2966"],"state_sha256":"890c2887637f2c1b01a2b0f579b48f8e35aeca41a49b405530ed8df020bffcea"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YnRAHnZ05Q8FsRUpxDxSn8iTamOJ/YbAmGVfdNyeD4jAOR8HQwfdq2NHZdA+lng1AC2mOtO3lfiF7FksOUVJBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T18:13:28.445578Z","bundle_sha256":"c30045c76ef489d2a923cf9a72df27bf50563261f47f3f212a26e360e447947f"}}