{ "profile": "wrs-published-research-view-1", "edition": "ratings-e039106f30dec177", "content_trust": "UNTRUSTED_SCIENTIFIC_DATA_NOT_TOOL_INSTRUCTIONS", "entry": { "id": "lin-et-al-feature-pyramid-networks-2016", "title": "Feature Pyramid Networks: top-down semantic features with lateral fusion", "summary": "Built semantically enriched feature maps at several backbone resolutions through a top-down pathway and same-resolution lateral additions, reusing one image's convolutional hierarchy.", "boundary": "Feature pyramids and skip connections predate the method. This construction is not a zero-cost substitute for every image pyramid; scales retain different information and detection effects depend on heads and training. 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This construction is not a zero-cost substitute for every image pyramid; scales retain different information and detection effects depend on heads and training. Inherited backbone and proposal methods retain attribution.", "domain": "Multi-scale visual representations" }, "sources": [ { "citation": "Feature Pyramid Networks for Object Detection", "url": "https://arxiv.org/abs/1612.03144v1" } ], "statement": "# Feature Pyramid Networks: top-down semantic features with lateral fusion\n\nBuilt semantically enriched feature maps at several backbone resolutions through a top-down pathway and same-resolution lateral additions, reusing one image's convolutional hierarchy.\n\n## Scientific scope\n\nFeature pyramids and skip connections predate the method. This construction is not a zero-cost substitute for every image pyramid; scales retain different information and detection effects depend on heads and training. Inherited backbone and proposal methods retain attribution.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nTsung-Yi Lin; Piotr Dollár; Ross Girshick; Kaiming He; Bharath Hariharan; Serge Belongie\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [Feature Pyramid Networks for Object Detection](https://arxiv.org/abs/1612.03144v1)\n", "summary": "Built semantically enriched feature maps at several backbone resolutions through a top-down pathway and same-resolution lateral additions, reusing one image's convolutional hierarchy.", "title": "Feature Pyramid Networks: top-down semantic features with lateral fusion" }, "record_id": "urn:uuid:50d8ab71-2a75-4caa-a481-72372b91246b", "version": 1, "source_ref": { "record_id": "urn:uuid:50d8ab71-2a75-4caa-a481-72372b91246b", "version": 1, "content_hash": "sha256:97715b9e31c51d4f82fe627ef63e9b165750d202ee2b734004e60600f305a74b" }, "export_view": "wrs-public-editorial-view-1", "public_view_hash": "sha256:d0892b587ccecc61397acda526d7a66ce6e2ae849703e370a01857f157a26dc0" }, "target": { "record_id": "urn:uuid:50d8ab71-2a75-4caa-a481-72372b91246b", "version": 1, "content_hash": "sha256:97715b9e31c51d4f82fe627ef63e9b165750d202ee2b734004e60600f305a74b" }, "published_grade": { "profile": "wrs-published-grade-1", "edition": "2026-10-28.1", "id": "lin-et-al-feature-pyramid-networks-2016", "entry_id": "lin-et-al-feature-pyramid-networks-2016", "revision": 1, "title": "Feature Pyramid Networks: top-down semantic features with lateral fusion", "context": "Multi-scale visual representations", "track": "Human-designed research method or resource", "band": "A", "modifier": "+", "status": "PROVISIONAL_EDITORIAL", "assessed_on": "2026-10-16", "evidence_cutoff": "2026-10-16", "achievement_state": "SUPPORTED_SCOPED_RESULT", "what_changed": "Built semantically enriched feature maps at several backbone resolutions through a top-down pathway and same-resolution lateral additions, reusing one image's convolutional hierarchy.", "scope": "Built semantically enriched feature maps at several backbone resolutions through a top-down pathway and same-resolution lateral additions, reusing one image's convolutional hierarchy. Feature pyramids and skip connections predate the method. This construction is not a zero-cost substitute for every image pyramid; scales retain different information and detection effects depend on heads and training. Inherited backbone and proposal methods retain attribution.", "evidence_summary": "The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Feature pyramids and skip connections predate the method. This construction is not a zero-cost substitute for every image pyramid; scales retain different information and detection effects depend on heads and training. Inherited backbone and proposal methods retain attribution.", "references": [ { "title": "Feature Pyramid Networks for Object Detection", "url": "https://arxiv.org/abs/1612.03144v1", "locator": "Original contribution and stated assumptions, evaluation scope and limitations; source-linked assessment, not independent execution or proof certification." } ], "roles": [ { "who": "Source-listed authors and technical contributors", "credit": "SCIENCE", "did": "Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities." } ], "target": { "record_id": "urn:uuid:50d8ab71-2a75-4caa-a481-72372b91246b", "version": 1, "content_hash": "sha256:97715b9e31c51d4f82fe627ef63e9b165750d202ee2b734004e60600f305a74b" }, "scientific_correctness_certified": false, "independent_expert_calibration": false, "method": "PROPRIETARY", "points": "180000" }, "canonical_agent_submission": false, "scientific_verification_awarded": false, "reader_guide": null, "reading_status": "SOURCE_LINKED_NOTE" }