{"ID":2852121,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.18409","arxiv_id":"2510.18409","title":"How2Compress: Scalable and Efficient Edge Video Analytics via Adaptive Granular Video Compression","abstract":"With the rapid proliferation of the Internet of Things, video analytics has become a cornerstone application in wireless multimedia sensor networks. To support such applications under bandwidth constraints, learning-based adaptive quantization for video compression have demonstrated strong potential in reducing bitrate while maintaining analytical accuracy. However, existing frameworks often fail to fully exploit the fine-grained quality control enabled by modern blockbased video codecs, leaving significant compression efficiency untapped. In this paper, we present How2Compress, a simple yet effective framework designed to enhance video compression efficiency through precise, fine-grained quality control at the macroblock level. How2Compress is a plug-and-play module and can be seamlessly integrated into any existing edge video analytics pipelines. We implement How2Compress on the H.264 codec and evaluate its performance across diverse real-world scenarios. Experimental results show that How2Compress achieves up to $50.4\\%$ bitrate savings and outperforms baselines by up to $3.01\\times$ without compromising accuracy, demonstrating its practical effectiveness and efficiency. Code is available at https://github.com/wyhallenwu/how2compress and a reproducible docker image at https://hub.docker.com/r/wuyuheng/how2compress.","short_abstract":"With the rapid proliferation of the Internet of Things, video analytics has become a cornerstone application in wireless multimedia sensor networks. To support such applications under bandwidth constraints, learning-based adaptive quantization for video compression have demonstrated strong potential in reducing bitrate...","url_abs":"https://arxiv.org/abs/2510.18409","url_pdf":"https://arxiv.org/pdf/2510.18409v1","authors":"[\"Yuheng Wu\",\"Thanh-Tung Nguyen\",\"Lucas Liebe\",\"Quang Tau\",\"Pablo Espinosa Campos\",\"Jinghan Cheng\",\"Dongman Lee\"]","published":"2025-10-21T08:32:48Z","proceeding":"cs.MM","tasks":"[\"cs.MM\",\"cs.NI\"]","methods":"[]","project_urls":"[\"https://hub.docker.com/r/wuyuheng/how2compress\"]","has_code":false,"code_links":[{"ID":607966,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2852121,"paper_url":"https://arxiv.org/abs/2510.18409","paper_title":"How2Compress: Scalable and Efficient Edge Video Analytics via Adaptive Granular Video Compression","repo_url":"https://github.com/wyhallenwu/how2compress","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}