{"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/eurnet-efficient-multi-range-relational","title":"EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data","arxiv_id":"2211.12941","date":"2022-11-23","proceeding":null,"authors":["Minghao Xu","Yuanfan Guo","Yi Xu","Jian Tang","Xinlei Chen","Yuandong Tian"],"abstract":"Modeling spatial relationship in the data remains critical across many different tasks, such as image classification, semantic segmentation and protein structure understanding. Previous works often use a unified solution like relative positional encoding. However, there exists different kinds of spatial relations, including short-range, medium-range and long-range relations, and modeling them separately can better capture the focus of different tasks on the multi-range relations (e.g., short-range relations can be important in instance segmentation, while long-range relations should be upweighted for semantic segmentation). In this work, we introduce the EurNet for Efficient multi-range relational modeling. EurNet constructs the multi-relational graph, where each type of edge corresponds to short-, medium- or long-range spatial interactions. In the constructed graph, EurNet adopts a novel modeling layer, called gated relational message passing (GRMP), to propagate multi-relational information across the data. GRMP captures multiple relations within the data with little extra computational cost. We study EurNets in two important domains for image and protein structure modeling. Extensive experiments on ImageNet classification, COCO object detection and ADE20K semantic segmentation verify the gains of EurNet over the previous SoTA FocalNet. On the EC and GO protein function prediction benchmarks, EurNet consistently surpasses the previous SoTA GearNet. Our results demonstrate the strength of EurNets on modeling spatial multi-relational data from various domains. The implementations of EurNet for image modeling are available at https://github.com/hirl-team/EurNet-Image . The implementations for other applied domains/tasks will be released soon.","url_abs":"https://arxiv.org/abs/2211.12941v1","url_pdf":"https://arxiv.org/pdf/2211.12941v1.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":"eurnet-efficient-multi-range-relational","repo_url":"https://github.com/hirl-team/eurnet-image","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"instance-segmentation","task_name":"Instance Segmentation"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"protein-function-prediction","task_name":"Protein Function Prediction"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"image-classification","task_name":"image-classification"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2211.12941","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2211.12941"}},"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/hirl-team/eurnet-image","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"ran":1,"unverified":8},"by_repo_kind":{"official":{"samples":9,"ran":1,"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":"3dc19396537db789","entry":"all_reduce_mean","repo":"hirl-team/eurnet-image","repo_kind":"official","path":"eurnet/utils/dist.py","file_url":"https://github.com/hirl-team/eurnet-image/blob/HEAD/eurnet/utils/dist.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"3dc19396537db789"}},{"code_sha256_prefix":"b6e1824d78f8a850","entry":"add_quotation_to_string","repo":"hirl-team/eurnet-image","repo_kind":"official","path":"eurnet/utils/config_utils.py","file_url":"https://github.com/hirl-team/eurnet-image/blob/HEAD/eurnet/utils/config_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"b6e1824d78f8a850"}},{"code_sha256_prefix":"b0a5beb34716d5a6","entry":"check_keywords_in_name","repo":"hirl-team/eurnet-image","repo_kind":"official","path":"eurnet/utils/misc.py","file_url":"https://github.com/hirl-team/eurnet-image/blob/HEAD/eurnet/utils/misc.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"b0a5beb34716d5a6"}},{"code_sha256_prefix":"571021715428528c","entry":"get_2d_relative_pos_embed","repo":"hirl-team/eurnet-image","repo_kind":"official","path":"eurnet/utils/position_embed.py","file_url":"https://github.com/hirl-team/eurnet-image/blob/HEAD/eurnet/utils/position_embed.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"571021715428528c"}},{"code_sha256_prefix":"3185afc3e87293ed","entry":"get_2d_sincos_pos_embed","repo":"hirl-team/eurnet-image","repo_kind":"official","path":"eurnet/utils/position_embed.py","file_url":"https://github.com/hirl-team/eurnet-image/blob/HEAD/eurnet/utils/position_embed.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"3185afc3e87293ed"}},{"code_sha256_prefix":"f10004e059714d42","entry":"get_2d_sincos_pos_embed_from_grid","repo":"hirl-team/eurnet-image","repo_kind":"official","path":"eurnet/utils/position_embed.py","file_url":"https://github.com/hirl-team/eurnet-image/blob/HEAD/eurnet/utils/position_embed.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"f10004e059714d42"}},{"code_sha256_prefix":"33777b13e9f279e7","entry":"get_params_groups","repo":"hirl-team/eurnet-image","repo_kind":"official","path":"eurnet/utils/misc.py","file_url":"https://github.com/hirl-team/eurnet-image/blob/HEAD/eurnet/utils/misc.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"33777b13e9f279e7"}},{"code_sha256_prefix":"4f0fc1b40e2da4bc","entry":"is_number_or_bool_or_none","repo":"hirl-team/eurnet-image","repo_kind":"official","path":"eurnet/utils/config_utils.py","file_url":"https://github.com/hirl-team/eurnet-image/blob/HEAD/eurnet/utils/config_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"4f0fc1b40e2da4bc"}},{"code_sha256_prefix":"915ef88ed1bd4765","entry":"param_groups_lrd","repo":"hirl-team/eurnet-image","repo_kind":"official","path":"eurnet/utils/misc.py","file_url":"https://github.com/hirl-team/eurnet-image/blob/HEAD/eurnet/utils/misc.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"915ef88ed1bd4765"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}