{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/concl-concept-contrastive-learning-for-dense","title":"ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Images","arxiv_id":"2207.06733","date":"2022-07-14","proceeding":null,"authors":["Jiawei Yang","Hanbo Chen","Yuan Liang","Junzhou Huang","Lei He","Jianhua Yao"],"abstract":"Detectingandsegmentingobjectswithinwholeslideimagesis essential in computational pathology workflow. Self-supervised learning (SSL) is appealing to such annotation-heavy tasks. Despite the extensive benchmarks in natural images for dense tasks, such studies are, unfortunately, absent in current works for pathology. Our paper intends to narrow this gap. We first benchmark representative SSL methods for dense prediction tasks in pathology images. Then, we propose concept contrastive learning (ConCL), an SSL framework for dense pre-training. We explore how ConCL performs with concepts provided by different sources and end up with proposing a simple dependency-free concept generating method that does not rely on external segmentation algorithms or saliency detection models. Extensive experiments demonstrate the superiority of ConCL over previous state-of-the-art SSL methods across different settings. Along our exploration, we distll several important and intriguing components contributing to the success of dense pre-training for pathology images. We hope this work could provide useful data points and encourage the community to conduct ConCL pre-training for problems of interest. Code is available.","url_abs":"https://arxiv.org/abs/2207.06733v1","url_pdf":"https://arxiv.org/pdf/2207.06733v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"concl-concept-contrastive-learning-for-dense","repo_url":"https://github.com/tencentailabhealthcare/concl","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"contrastive-learning","task_name":"Contrastive Learning"},{"task_slug":"saliency-detection","task_name":"Saliency Detection"},{"task_slug":"self-supervised-learning","task_name":"Self-Supervised Learning"}],"methods":[{"method_slug":"contrastive-learning","method_name":"Contrastive Learning"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2207.06733","atlas_url":"https://app.syntology.ai/?focus=2207.06733","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2207.06733"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"deterministic:regex_extraction","url":"https://github.com/TencentAILabHealthcare/ConCL","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran":2,"unverified":3},"by_repo_kind":{"official":{"samples":5,"ran":2,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"9f4986d64070dbd6","entry":"batch_cosine_KMeans","repo":"TencentAILabHealthcare/ConCL","repo_kind":"official","path":"openselfsup/models/concl.py","file_url":"https://github.com/TencentAILabHealthcare/ConCL/blob/HEAD/openselfsup/models/concl.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"9f4986d64070dbd6"}},{"code_sha256_prefix":"8b8c31a24a1755e6","entry":"concat_all_gather_v2","repo":"TencentAILabHealthcare/ConCL","repo_kind":"official","path":"openselfsup/models/concl.py","file_url":"https://github.com/TencentAILabHealthcare/ConCL/blob/HEAD/openselfsup/models/concl.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"8b8c31a24a1755e6"}},{"code_sha256_prefix":"73cecca9f3575f09","entry":"concat_all_gather","repo":"TencentAILabHealthcare/ConCL","repo_kind":"official","path":"openselfsup/models/densecl.py","file_url":"https://github.com/TencentAILabHealthcare/ConCL/blob/HEAD/openselfsup/models/densecl.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"73cecca9f3575f09"}},{"code_sha256_prefix":"3068b49e32832036","entry":"concat_all_gather","repo":"TencentAILabHealthcare/ConCL","repo_kind":"official","path":"openselfsup/models/moco.py","file_url":"https://github.com/TencentAILabHealthcare/ConCL/blob/HEAD/openselfsup/models/moco.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"3068b49e32832036"}},{"code_sha256_prefix":"46fea249f3007035","entry":"concat_all_gather","repo":"TencentAILabHealthcare/ConCL","repo_kind":"official","path":"openselfsup/models/concl.py","file_url":"https://github.com/TencentAILabHealthcare/ConCL/blob/HEAD/openselfsup/models/concl.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"46fea249f3007035"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}