{"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-class-model-fitting-by-energy","title":"Multi-Class Model Fitting by Energy Minimization and Mode-Seeking","arxiv_id":"1706.00827","date":"2017-06-02","proceeding":"ECCV 2018 9","authors":["Daniel Barath","Jiri Matas"],"abstract":"We propose a general formulation, called Multi-X, for multi-class\nmulti-instance model fitting - the problem of interpreting the input data as a\nmixture of noisy observations originating from multiple instances of multiple\nclasses. We extend the commonly used alpha-expansion-based technique with a new\nmove in the label space. The move replaces a set of labels with the\ncorresponding density mode in the model parameter domain, thus achieving fast\nand robust optimization. Key optimization parameters like the bandwidth of the\nmode seeking are set automatically within the algorithm. Considering that a\ngroup of outliers may form spatially coherent structures in the data, we\npropose a cross-validation-based technique removing statistically insignificant\ninstances. Multi-X outperforms significantly the state-of-the-art on publicly\navailable datasets for diverse problems: multiple plane and rigid motion\ndetection; motion segmentation; simultaneous plane and cylinder fitting; circle\nand line fitting.","url_abs":"http://arxiv.org/abs/1706.00827v2","url_pdf":"http://arxiv.org/pdf/1706.00827v2.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-class-model-fitting-by-energy","repo_url":"https://github.com/danini/multi-x","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"motion-detection","task_name":"Motion Detection"},{"task_slug":"motion-segmentation","task_name":"Motion Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1706.00827","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}