{"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/multi-scale-convolutional-neural-networks-for-1","title":"Multi-scale Convolutional Neural Networks for Crowd Counting","arxiv_id":"1702.02359","date":"2017-02-08","proceeding":null,"authors":["Lingke Zeng","Xiangmin Xu","Bolun Cai","Suo Qiu","Tong Zhang"],"abstract":"Crowd counting on static images is a challenging problem due to scale\nvariations. Recently deep neural networks have been shown to be effective in\nthis task. However, existing neural-networks-based methods often use the\nmulti-column or multi-network model to extract the scale-relevant features,\nwhich is more complicated for optimization and computation wasting. To this\nend, we propose a novel multi-scale convolutional neural network (MSCNN) for\nsingle image crowd counting. Based on the multi-scale blobs, the network is\nable to generate scale-relevant features for higher crowd counting performances\nin a single-column architecture, which is both accuracy and cost effective for\npractical applications. Complemental results show that our method outperforms\nthe state-of-the-art methods on both accuracy and robustness with far less\nnumber of parameters.","url_abs":"http://arxiv.org/abs/1702.02359v1","url_pdf":"http://arxiv.org/pdf/1702.02359v1.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":"multi-scale-convolutional-neural-networks-for-1","repo_url":"https://github.com/Ling-Bao/mscnn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"crowd-counting","task_name":"Crowd Counting"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1702.02359","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}