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In this report, we explore the application of SAM in Weakly-Supervised Semantic Segmentation (WSSS). Particularly, we adapt SAM as the pseudo-label generation pipeline given only the image-level class labels. While we observed impressive results in most cases, we also identify certain limitations. Our study includes performance evaluations on PASCAL VOC and MS-COCO, where we achieved remarkable improvements over the latest state-of-the-art methods on both datasets. We anticipate that this report encourages further explorations of adopting SAM in WSSS, as well as wider real-world applications.","url_abs":"https://arxiv.org/abs/2305.01586v2","url_pdf":"https://arxiv.org/pdf/2305.01586v2.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":"an-alternative-to-wsss-an-empirical-study-of","repo_url":"https://github.com/weixuansun/wsss_sam","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"pseudo-label","task_name":"Pseudo Label"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"weakly-supervised-semantic-segmentation-1","task_name":"Weakly supervised Semantic Segmentation"},{"task_slug":"weakly-supervised-semantic-segmentation","task_name":"Weakly-Supervised Semantic Segmentation"}],"methods":[{"method_slug":"sam","method_name":"SAM"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/weakly-supervised-semantic-segmentation-on-4","task":"Weakly-Supervised Semantic Segmentation","dataset":"COCO 2014 val","model":"WSSS-SAM(DeepLabV2-ResNet101)","rank_in_archive_order":3,"of":39,"metrics":{"mIoU":"55.6"},"uses_additional_data":true},{"leaderboard":"/sota/weakly-supervised-semantic-segmentation-on-1","task":"Weakly-Supervised Semantic Segmentation","dataset":"PASCAL VOC 2012 test","model":"WSSS-SAM(DeepLabV2-ResNet101)","rank_in_archive_order":6,"of":60,"metrics":{"Mean IoU":"77.1"},"uses_additional_data":true},{"leaderboard":"/sota/weakly-supervised-semantic-segmentation-on","task":"Weakly-Supervised Semantic Segmentation","dataset":"PASCAL VOC 2012 val","model":"WSSS-SAM(ResNet-101, multi-stage)","rank_in_archive_order":7,"of":73,"metrics":{"Mean IoU":"77.2"},"uses_additional_data":true}],"syntology":{"syntology_url":"https://syntology.ai/paper/2305.01586","atlas_url":"https://app.syntology.ai/?focus=2305.01586","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.01586"}},"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. 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