{"url":"/method/arshoe","slug":"arshoe","name":"ARShoe","full_name":"ARShoe","full_name_withheld":false,"description_markdown":"**ARShoe** is a multi-branch network for pose estimation and segmentation tackling the \"try-on\" problem for augmented reality shoes. Consisting of an encoder and a decoder, the multi-branch network is trained to predict keypoints [heatmap](https://paperswithcode.com/method/heatmap) (heatmap), [PAFs](https://paperswithcode.com/method/pafs) heatmap (pafmap), and segmentation results (segmap) simultaneously. Post processes are then performed for a smooth and realistic virtual try-on.","description_state":"present","introduced_year":null,"introduced_by":{"title":"ARShoe: Real-Time Augmented Reality Shoe Try-on System on Smartphones","paper":"/paper/arshoe-real-time-augmented-reality-shoe-try","first_author":"Shan An","n_authors":10,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/arshoe-real-time-augmented-reality-shoe-try"},"source":{"url":"https://arxiv.org/abs/2108.10515v1","title":"ARShoe: Real-Time Augmented Reality Shoe Try-on System on Smartphones","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Augmented Reality Methods","url":"/methods/category/augmented-reality-methods","pwc_aliases":[]},{"area":"Computer Vision","area_id":"computer-vision","collection":"6D Pose Estimation Models","url":"/methods/category/6d-pose-estimation-models","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":1,"papers_newest_first":[{"paper":"/paper/arshoe-real-time-augmented-reality-shoe-try","title":"ARShoe: Real-Time Augmented Reality Shoe Try-on System on Smartphones","date":"2021-08-24","arxiv_id":"2108.10515","n_code_links":0,"syntology":null}],"papers_shown":1,"tasks":[{"task":"/task/pose-estimation","name":"Pose Estimation","papers":1},{"task":"/task/virtual-try-on","name":"Virtual Try-on","papers":1}],"tasks_shown":2,"n_tasks":2,"usage_by_year":[{"year":"2021","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/arshoe"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}