{"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/dynamic-dictionary-learning-for-remote","title":"Dynamic Dictionary Learning for Remote Sensing Image Segmentation","arxiv_id":"2503.06683","date":"2025-03-09","proceeding":null,"authors":["Xuechao Zou","Yue Li","Shun Zhang","Kai Li","Shiying Wang","Pin Tao","Junliang Xing","Congyan Lang"],"abstract":"Remote sensing image segmentation faces persistent challenges in distinguishing morphologically similar categories and adapting to diverse scene variations. While existing methods rely on implicit representation learning paradigms, they often fail to dynamically adjust semantic embeddings according to contextual cues, leading to suboptimal performance in fine-grained scenarios such as cloud thickness differentiation. This work introduces a dynamic dictionary learning framework that explicitly models class ID embeddings through iterative refinement. The core contribution lies in a novel dictionary construction mechanism, where class-aware semantic embeddings are progressively updated via multi-stage alternating cross-attention querying between image features and dictionary embeddings. This process enables adaptive representation learning tailored to input-specific characteristics, effectively resolving ambiguities in intra-class heterogeneity and inter-class homogeneity. To further enhance discriminability, a contrastive constraint is applied to the dictionary space, ensuring compact intra-class distributions while maximizing inter-class separability. Extensive experiments across both coarse- and fine-grained datasets demonstrate consistent improvements over state-of-the-art methods, particularly in two online test benchmarks (LoveDA and UAVid). Code is available at https://anonymous.4open.science/r/D2LS-8267/.","url_abs":"https://arxiv.org/abs/2503.06683v1","url_pdf":"https://arxiv.org/pdf/2503.06683v1.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":"dynamic-dictionary-learning-for-remote","repo_url":"https://github.com/XavierJiezou/D2LS","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"dictionary-learning","task_name":"Dictionary Learning"},{"task_slug":"image-segmentation","task_name":"Image Segmentation"},{"task_slug":"representation-learning","task_name":"Representation Learning"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/semantic-segmentation-on-fine-grained-cloud","task":"Semantic Segmentation","dataset":"Fine-Grained Cloud Segmentation Dataset","model":"D2LS","rank_in_archive_order":1,"of":4,"metrics":{"mIoU":"82.16"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-fine-grained-grass","task":"Semantic Segmentation","dataset":"Fine-Grained Grass Segmentation Dataset","model":"D2LS","rank_in_archive_order":1,"of":10,"metrics":{"mIoU":"51.96"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-isprs-potsdam","task":"Semantic Segmentation","dataset":"ISPRS Potsdam","model":"D2LS","rank_in_archive_order":18,"of":20,"metrics":{"Mean F1":"94.7"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-isprs-vaihingen","task":"Semantic Segmentation","dataset":"ISPRS Vaihingen","model":"D2LS","rank_in_archive_order":11,"of":12,"metrics":{"Average F1":"91.9"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-loveda","task":"Semantic Segmentation","dataset":"LoveDA","model":"D2LS","rank_in_archive_order":2,"of":19,"metrics":{"Category mIoU":"55.3"},"uses_additional_data":false},{"leaderboard":"/sota/semantic-segmentation-on-uavid","task":"Semantic Segmentation","dataset":"UAVid","model":"D2LS","rank_in_archive_order":3,"of":10,"metrics":{"Mean IoU":"70.9"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2503.06683","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.06683"}},"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":"deterministic:regex_extraction","url":"https://github.com/XavierJiezou/D2LS","reach":null}],"summary":{"ran":8,"ran_draft_wrong":1,"unverified":3},"by_repo_kind":{"listed":{"samples":12,"ran":9,"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":12,"samples":[{"code_sha256_prefix":"e843618eb9a8862f","entry":"Attention","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"e843618eb9a8862f"}},{"code_sha256_prefix":"781ef174b1c49d2b","entry":"DynamicQueryModule","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"781ef174b1c49d2b"}},{"code_sha256_prefix":"4b7c224955639e01","entry":"FeatureMLP","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"4b7c224955639e01"}},{"code_sha256_prefix":"36de7725ad04a727","entry":"InteractorBlock","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"36de7725ad04a727"}},{"code_sha256_prefix":"02ffe882b76bbe14","entry":"MLP","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"02ffe882b76bbe14"}},{"code_sha256_prefix":"79e97de4160f8c65","entry":"MLPBlock","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"79e97de4160f8c65"}},{"code_sha256_prefix":"44fe47cdadab4c9b","entry":"Modulator","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"44fe47cdadab4c9b"}},{"code_sha256_prefix":"fc19d6016ab36004","entry":"PositionEmbeddingRandom","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"fc19d6016ab36004"}},{"code_sha256_prefix":"84616a9dbac09f3a","entry":"compute_contrastive_loss","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"84616a9dbac09f3a"}},{"code_sha256_prefix":"6757fe71e7f3103c","entry":"Decoder","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"6757fe71e7f3103c"}},{"code_sha256_prefix":"0ac3efb2b9fdeaea","entry":"DynamicDictionaryLearning","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"0ac3efb2b9fdeaea"}},{"code_sha256_prefix":"533403e7ca0d3d4c","entry":"Interactor","repo":"XavierJiezou/D2LS","repo_kind":"listed","path":"network/models/d2ls.py","file_url":"https://github.com/XavierJiezou/D2LS/blob/HEAD/network/models/d2ls.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"533403e7ca0d3d4c"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}