{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:HZBY7N3HYYZ3F7ZSRBQT4WX7OE","short_pith_number":"pith:HZBY7N3H","schema_version":"1.0","canonical_sha256":"3e438fb767c633b2ff3288613e5aff710d764a4ab3a6221f080c57ae340c26d1","source":{"kind":"arxiv","id":"2108.06337","version":1},"attestation_state":"computed","paper":{"title":"Dual Path Learning for Domain Adaptation of Semantic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dong Chen, Fang Wen, Fangyun Wei, Jianmin Bao, Wenqiang Zhang, Yiting Cheng","submitted_at":"2021-08-13T17:59:55Z","abstract_excerpt":"Domain adaptation for semantic segmentation enables to alleviate the need for large-scale pixel-wise annotations. Recently, self-supervised learning (SSL) with a combination of image-to-image translation shows great effectiveness in adaptive segmentation. The most common practice is to perform SSL along with image translation to well align a single domain (the source or target). However, in this single-domain paradigm, unavoidable visual inconsistency raised by image translation may affect subsequent learning. In this paper, based on the observation that domain adaptation frameworks performed "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2108.06337","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-13T17:59:55Z","cross_cats_sorted":[],"title_canon_sha256":"a8aa77583ae8f63565525d716eeeff92c42fe13bb822f6d2bcf886d7e5a27cd9","abstract_canon_sha256":"1f8ae9a3fb9c30b161ed8af854e4279e72fdaebe682e4df3f229df63ecd4a0c0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:05:39.842753Z","signature_b64":"AxFLBoCmLM2MhbPK88h3hzPEqnOlnuwMqtMB4UxG49UP5i60rz77kDyK3GGHb4KXTWBpa9RDUqJXSVJqF2F5AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e438fb767c633b2ff3288613e5aff710d764a4ab3a6221f080c57ae340c26d1","last_reissued_at":"2026-07-05T03:05:39.842275Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:05:39.842275Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dual Path Learning for Domain Adaptation of Semantic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dong Chen, Fang Wen, Fangyun Wei, Jianmin Bao, Wenqiang Zhang, Yiting Cheng","submitted_at":"2021-08-13T17:59:55Z","abstract_excerpt":"Domain adaptation for semantic segmentation enables to alleviate the need for large-scale pixel-wise annotations. Recently, self-supervised learning (SSL) with a combination of image-to-image translation shows great effectiveness in adaptive segmentation. The most common practice is to perform SSL along with image translation to well align a single domain (the source or target). However, in this single-domain paradigm, unavoidable visual inconsistency raised by image translation may affect subsequent learning. In this paper, based on the observation that domain adaptation frameworks performed "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.06337","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2108.06337/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2108.06337","created_at":"2026-07-05T03:05:39.842341+00:00"},{"alias_kind":"arxiv_version","alias_value":"2108.06337v1","created_at":"2026-07-05T03:05:39.842341+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.06337","created_at":"2026-07-05T03:05:39.842341+00:00"},{"alias_kind":"pith_short_12","alias_value":"HZBY7N3HYYZ3","created_at":"2026-07-05T03:05:39.842341+00:00"},{"alias_kind":"pith_short_16","alias_value":"HZBY7N3HYYZ3F7ZS","created_at":"2026-07-05T03:05:39.842341+00:00"},{"alias_kind":"pith_short_8","alias_value":"HZBY7N3H","created_at":"2026-07-05T03:05:39.842341+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HZBY7N3HYYZ3F7ZSRBQT4WX7OE","json":"https://pith.science/pith/HZBY7N3HYYZ3F7ZSRBQT4WX7OE.json","graph_json":"https://pith.science/api/pith-number/HZBY7N3HYYZ3F7ZSRBQT4WX7OE/graph.json","events_json":"https://pith.science/api/pith-number/HZBY7N3HYYZ3F7ZSRBQT4WX7OE/events.json","paper":"https://pith.science/paper/HZBY7N3H"},"agent_actions":{"view_html":"https://pith.science/pith/HZBY7N3HYYZ3F7ZSRBQT4WX7OE","download_json":"https://pith.science/pith/HZBY7N3HYYZ3F7ZSRBQT4WX7OE.json","view_paper":"https://pith.science/paper/HZBY7N3H","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2108.06337&json=true","fetch_graph":"https://pith.science/api/pith-number/HZBY7N3HYYZ3F7ZSRBQT4WX7OE/graph.json","fetch_events":"https://pith.science/api/pith-number/HZBY7N3HYYZ3F7ZSRBQT4WX7OE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HZBY7N3HYYZ3F7ZSRBQT4WX7OE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HZBY7N3HYYZ3F7ZSRBQT4WX7OE/action/storage_attestation","attest_author":"https://pith.science/pith/HZBY7N3HYYZ3F7ZSRBQT4WX7OE/action/author_attestation","sign_citation":"https://pith.science/pith/HZBY7N3HYYZ3F7ZSRBQT4WX7OE/action/citation_signature","submit_replication":"https://pith.science/pith/HZBY7N3HYYZ3F7ZSRBQT4WX7OE/action/replication_record"}},"created_at":"2026-07-05T03:05:39.842341+00:00","updated_at":"2026-07-05T03:05:39.842341+00:00"}