{"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/edgeflow-achieving-practical-interactive","title":"EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow","arxiv_id":"2109.09406","date":"2021-09-20","proceeding":null,"authors":["Yuying Hao","Yi Liu","Zewu Wu","Lin Han","Yizhou Chen","Guowei Chen","Lutao Chu","Shiyu Tang","Zhiliang Yu","Zeyu Chen","Baohua Lai"],"abstract":"High-quality training data play a key role in image segmentation tasks. Usually, pixel-level annotations are expensive, laborious and time-consuming for the large volume of training data. To reduce labelling cost and improve segmentation quality, interactive segmentation methods have been proposed, which provide the result with just a few clicks. However, their performance does not meet the requirements of practical segmentation tasks in terms of speed and accuracy. In this work, we propose EdgeFlow, a novel architecture that fully utilizes interactive information of user clicks with edge-guided flow. Our method achieves state-of-the-art performance without any post-processing or iterative optimization scheme. Comprehensive experiments on benchmarks also demonstrate the superiority of our method. In addition, with the proposed method, we develop an efficient interactive segmentation tool for practical data annotation tasks. The source code and tool is avaliable at https://github.com/PaddlePaddle/PaddleSeg.","url_abs":"https://arxiv.org/abs/2109.09406v2","url_pdf":"https://arxiv.org/pdf/2109.09406v2.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":"edgeflow-achieving-practical-interactive","repo_url":"https://github.com/PaddlePaddle/PaddleSeg","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"paddle","reach":null},{"paper_slug":"edgeflow-achieving-practical-interactive","repo_url":"https://github.com/PaddleCV-SIG/EISeg","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"paddle","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"edgeflow-achieving-practical-interactive","repo_url":"https://github.com/ihomeava/PaddleSeg2","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"paddle","reach":null}],"tasks":[{"task_slug":"image-segmentation","task_name":"Image Segmentation"},{"task_slug":"interactive-segmentation","task_name":"Interactive Segmentation"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[{"method_slug":"1x1-convolution","method_name":"1x1 Convolution"},{"method_slug":"batch-normalization","method_name":"Batch Normalization"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"dilated-convolution","method_name":"Dilated Convolution"},{"method_slug":"edgeflow","method_name":"EdgeFlow"},{"method_slug":"hrnet","method_name":"HRNet"},{"method_slug":"relu","method_name":"ReLU"},{"method_slug":"residual-connection","method_name":"Residual Connection"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/interactive-segmentation-on-berkeley","task":"Interactive Segmentation","dataset":"Berkeley","model":"EdgeFlow","rank_in_archive_order":8,"of":14,"metrics":{"NoC@90":"2.4"},"uses_additional_data":false},{"leaderboard":"/sota/interactive-segmentation-on-davis","task":"Interactive Segmentation","dataset":"DAVIS","model":"EdgeFlow","rank_in_archive_order":9,"of":15,"metrics":{"NoC@85":"4.54","NoC@90":"5.77"},"uses_additional_data":false},{"leaderboard":"/sota/interactive-segmentation-on-grabcut","task":"Interactive Segmentation","dataset":"GrabCut","model":"EdgeFlow","rank_in_archive_order":8,"of":18,"metrics":{"NoC@85":"1.6","NoC@90":"1.72"},"uses_additional_data":false},{"leaderboard":"/sota/interactive-segmentation-on-pascal-voc","task":"Interactive Segmentation","dataset":"PASCAL VOC","model":"EdgeFlow","rank_in_archive_order":2,"of":2,"metrics":{"NoC@85":"2.5"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2109.09406","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.09406"}},"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/PaddlePaddle/PaddleSeg","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/PaddleCV-SIG/EISeg","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/ihomeava/PaddleSeg2","reach":null}],"summary":{"ran_draft_wrong":2,"unverified":3},"by_repo_kind":{"official":{"samples":1,"ran":1,"repositories":1},"listed":{"samples":4,"ran":1,"repositories":2}},"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":"f07c554d3507b9b4","entry":"parse_configs","repo":"PaddlePaddle/PaddleSeg","repo_kind":"official","path":"EISeg/eiseg/util/config.py","file_url":"https://github.com/PaddlePaddle/PaddleSeg/blob/HEAD/EISeg/eiseg/util/config.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"f07c554d3507b9b4"}},{"code_sha256_prefix":"2f75a098ce9f7b0e","entry":"partition_list","repo":"ihomeava/PaddleSeg2","repo_kind":"listed","path":"contrib/Matting/core/predict.py","file_url":"https://github.com/ihomeava/PaddleSeg2/blob/HEAD/contrib/Matting/core/predict.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"2f75a098ce9f7b0e"}},{"code_sha256_prefix":"65d4c04ac1874b4a","entry":"expand_bbox","repo":"PaddleCV-SIG/EISeg","repo_kind":"listed","path":"eiseg/util/misc.py","file_url":"https://github.com/PaddleCV-SIG/EISeg/blob/HEAD/eiseg/util/misc.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":"65d4c04ac1874b4a"}},{"code_sha256_prefix":"4cc796e4c702610b","entry":"get_bbox_from_mask","repo":"PaddleCV-SIG/EISeg","repo_kind":"listed","path":"eiseg/util/misc.py","file_url":"https://github.com/PaddleCV-SIG/EISeg/blob/HEAD/eiseg/util/misc.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":"4cc796e4c702610b"}},{"code_sha256_prefix":"7676541fe9b404ec","entry":"get_dims_with_exclusion","repo":"PaddleCV-SIG/EISeg","repo_kind":"listed","path":"eiseg/util/misc.py","file_url":"https://github.com/PaddleCV-SIG/EISeg/blob/HEAD/eiseg/util/misc.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":"7676541fe9b404ec"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}