{"ID":3004819,"CreatedAt":"2026-06-03T03:09:48.883664427Z","UpdatedAt":"2026-06-05T11:43:53.432517148Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.03646","arxiv_id":"2606.03646","title":"A Benchmark for Semi-supervised Multi-modal Crowd Counting","abstract":"This paper constructs the first benchmark on semi-supervised multi-modal crowd counting. To lay the foundation for this unexplored task, we first formulate the semi-supervised multi-modal setting and a standardized protocol that specifies the labeled-unlabeled data partition across different labeled ratios. Next, to establish solid reference points, we carefully tailor a diverse set of representative baselines, including existing fully supervised multi-modal methods and semi-supervised single-modal methods. Then, we carefully evaluate their performance under our proposed benchmark. Codes and the data partition will be released on https://github.com/HenryCilence/Semi-supervised-Multimodal-Crowd-Counting.","short_abstract":"This paper constructs the first benchmark on semi-supervised multi-modal crowd counting. To lay the foundation for this unexplored task, we first formulate the semi-supervised multi-modal setting and a standardized protocol that specifies the labeled-unlabeled data partition across different labeled ratios. Next, to es...","url_abs":"https://arxiv.org/abs/2606.03646","url_pdf":"https://arxiv.org/pdf/2606.03646v1","authors":"[\"Haoliang Meng\",\"Xiaopeng Hong\",\"Yabin Wang\",\"Wangmeng Zuo\"]","published":"2026-06-02T13:38:41Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false,"code_links":[{"ID":612706,"CreatedAt":"2026-06-03T03:09:48.883664427Z","UpdatedAt":"2026-06-03T03:09:48.883664427Z","DeletedAt":null,"paper_id":3004819,"paper_url":"https://arxiv.org/abs/2606.03646","paper_title":"A Benchmark for Semi-supervised Multi-modal Crowd Counting","repo_url":"https://github.com/HenryCilence/Semi-supervised-Multimodal-Crowd-Counting","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}