{"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/point-to-box-network-for-accurate-object","title":"Point-to-Box Network for Accurate Object Detection via Single Point Supervision","arxiv_id":"2207.06827","date":"2022-07-14","proceeding":null,"authors":["Pengfei Chen","Xuehui Yu","Xumeng Han","Najmul Hassan","Kai Wang","Jiachen Li","Jian Zhao","Humphrey Shi","Zhenjun Han","Qixiang Ye"],"abstract":"Object detection using single point supervision has received increasing attention over the years. However, the performance gap between point supervised object detection (PSOD) and bounding box supervised detection remains large. In this paper, we attribute such a large performance gap to the failure of generating high-quality proposal bags which are crucial for multiple instance learning (MIL). To address this problem, we introduce a lightweight alternative to the off-the-shelf proposal (OTSP) method and thereby create the Point-to-Box Network (P2BNet), which can construct an inter-objects balanced proposal bag by generating proposals in an anchor-like way. By fully investigating the accurate position information, P2BNet further constructs an instance-level bag, avoiding the mixture of multiple objects. Finally, a coarse-to-fine policy in a cascade fashion is utilized to improve the IoU between proposals and ground-truth (GT). Benefiting from these strategies, P2BNet is able to produce high-quality instance-level bags for object detection. P2BNet improves the mean average precision (AP) by more than 50% relative to the previous best PSOD method on the MS COCO dataset. It also demonstrates the great potential to bridge the performance gap between point supervised and bounding-box supervised detectors. The code will be released at github.com/ucas-vg/P2BNet.","url_abs":"https://arxiv.org/abs/2207.06827v2","url_pdf":"https://arxiv.org/pdf/2207.06827v2.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":"point-to-box-network-for-accurate-object","repo_url":"https://github.com/ucas-vg/p2bnet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"point-to-box-network-for-accurate-object","repo_url":"https://github.com/ucas-vg/TinyBenchmark","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"point-to-box-network-for-accurate-object","repo_url":"https://github.com/ucas-vg/pointtinybenchmark","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"attribute","task_name":"Attribute"},{"task_slug":"multiple-instance-learning","task_name":"Multiple Instance Learning"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2207.06827","atlas_url":"https://app.syntology.ai/?focus=2207.06827","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2207.06827"}},"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/ucas-vg/P2BNet","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"ran":3},"by_repo_kind":{"official":{"samples":3,"ran":3,"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":"2268355e37eebb82","entry":"get_final_results","repo":"ucas-vg/P2BNet","repo_kind":"official","path":"TOV_mmdetection/.dev_scripts/gather_models.py","file_url":"https://github.com/ucas-vg/P2BNet/blob/HEAD/TOV_mmdetection/.dev_scripts/gather_models.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"2268355e37eebb82"}},{"code_sha256_prefix":"ae35528c6bd4bd1c","entry":"process_checkpoint","repo":"ucas-vg/P2BNet","repo_kind":"official","path":"TOV_mmdetection/.dev_scripts/gather_models.py","file_url":"https://github.com/ucas-vg/P2BNet/blob/HEAD/TOV_mmdetection/.dev_scripts/gather_models.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"ae35528c6bd4bd1c"}},{"code_sha256_prefix":"eb266541a2fb6b57","entry":"process_model_info","repo":"ucas-vg/P2BNet","repo_kind":"official","path":"TOV_mmdetection/.dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/ucas-vg/P2BNet/blob/HEAD/TOV_mmdetection/.dev_scripts/convert_test_benchmark_script.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"eb266541a2fb6b57"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}