{"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/can-sam-count-anything-an-empirical-study-on","title":"Can SAM Count Anything? An Empirical Study on SAM Counting","arxiv_id":"2304.10817","date":"2023-04-21","proceeding":null,"authors":["Zhiheng Ma","Xiaopeng Hong","Qinnan Shangguan"],"abstract":"Meta AI recently released the Segment Anything model (SAM), which has garnered attention due to its impressive performance in class-agnostic segmenting. In this study, we explore the use of SAM for the challenging task of few-shot object counting, which involves counting objects of an unseen category by providing a few bounding boxes of examples. We compare SAM's performance with other few-shot counting methods and find that it is currently unsatisfactory without further fine-tuning, particularly for small and crowded objects. Code can be found at \\url{https://github.com/Vision-Intelligence-and-Robots-Group/count-anything}.","url_abs":"https://arxiv.org/abs/2304.10817v1","url_pdf":"https://arxiv.org/pdf/2304.10817v1.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":"can-sam-count-anything-an-empirical-study-on","repo_url":"https://github.com/vision-intelligence-and-robots-group/count-anything","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"object-counting","task_name":"Object Counting"}],"methods":[{"method_slug":"sam","method_name":"SAM"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2304.10817","atlas_url":"https://app.syntology.ai/?focus=2304.10817","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}