{"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/self-supervised-learning-in-remote-sensing-a","title":"Self-supervised Learning in Remote Sensing: A Review","arxiv_id":"2206.13188","date":"2022-06-27","proceeding":null,"authors":["Yi Wang","Conrad M Albrecht","Nassim Ait Ali Braham","Lichao Mou","Xiao Xiang Zhu"],"abstract":"In deep learning research, self-supervised learning (SSL) has received great attention triggering interest within both the computer vision and remote sensing communities. While there has been a big success in computer vision, most of the potential of SSL in the domain of earth observation remains locked. In this paper, we provide an introduction to, and a review of the concepts and latest developments in SSL for computer vision in the context of remote sensing. Further, we provide a preliminary benchmark of modern SSL algorithms on popular remote sensing datasets, verifying the potential of SSL in remote sensing and providing an extended study on data augmentations. Finally, we identify a list of promising directions of future research in SSL for earth observation (SSL4EO) to pave the way for fruitful interaction of both domains.","url_abs":"https://arxiv.org/abs/2206.13188v2","url_pdf":"https://arxiv.org/pdf/2206.13188v2.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":"self-supervised-learning-in-remote-sensing-a","repo_url":"https://github.com/zhu-xlab/ssl4eo-review","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"self-supervised-learning-in-remote-sensing-a","repo_url":"https://github.com/hewanshrestha/why-self-supervision-in-time","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"self-supervised-learning-in-remote-sensing-a","repo_url":"https://github.com/zhu-xlab/dino-mm","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"earth-observation","task_name":"Earth Observation"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"multi-label-image-classification","task_name":"Multi-Label Image Classification"},{"task_slug":"self-supervised-learning","task_name":"Self-Supervised Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/image-classification-on-eurosat","task":"Image Classification","dataset":"EuroSAT","model":"MoCo-v2 (ResNet18, fine tune)","rank_in_archive_order":7,"of":15,"metrics":{"Accuracy (%)":"98.9"},"uses_additional_data":true},{"leaderboard":"/sota/image-classification-on-eurosat","task":"Image Classification","dataset":"EuroSAT","model":"MoCo-v2 (ResNet18, linear eval)","rank_in_archive_order":15,"of":15,"metrics":{"Accuracy (%)":"94.4"},"uses_additional_data":true},{"leaderboard":"/sota/multi-label-image-classification-on","task":"Multi-Label Image Classification","dataset":"BigEarthNet","model":"MoCo-v2 (ResNet18, fine tune)","rank_in_archive_order":3,"of":10,"metrics":{"mAP (micro)":"89.3","official split":"No"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2206.13188","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.13188"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+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":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/hewanshrestha/why-self-supervision-in-time","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/zhu-xlab/dino-mm","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/zhu-xlab/ssl4eo-review","reach":{"status":"ok"}}],"summary":{"ran_fixture":1},"by_repo_kind":{},"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":1,"samples":[{"code_sha256_prefix":"55120f2026b56aa2","entry":"drop_path","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"55120f2026b56aa2"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}