{"url":"/method/sample-redistribution","slug":"sample-redistribution","name":"Sample Redistribution","full_name":"Sample Redistribution","full_name_withheld":false,"description_markdown":"**Sample Redistribution** is a [data augmentation](https://paperswithcode.com/methods/category/image-data-augmentation) technique for face detection which augments training samples based on the statistics of benchmark datasets via large-scale cropping. During training data augmentation, square patches are cropped from the original images with a random size from the set $[0.3,1.0]$ of the short edge of the original images. To generate more positive samples for stride 8, the random size range is enlarged from $[0.3,1.0]$ to $[0.3,2.0]$. When the crop box is beyond the original image, average RGB values fill the missing pixels.\r\n\r\nThe motivation is that for efficient [face detection](https://paperswithcode.com/task/face-detection) under a fixed VGA resolution (i.e. 640×480), most of the faces (78.93%) in [WIDER FACE](https://paperswithcode.com/dataset/wider-face-1) are smaller than 32×32 pixels, and thus they are predicted by shallow stages. To obtain more training samples for these shallow stages, Sample Redistribution (SR) is used.","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":"https://arxiv.org/abs/2105.04714v1","title":"Sample and Computation Redistribution for Efficient Face Detection","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Image Data Augmentation","url":"/methods/category/image-data-augmentation","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":null,"papers_newest_first":[{"paper":"/paper/sample-and-computation-redistribution-for","title":"Sample and Computation Redistribution for Efficient Face Detection","date":"2021-05-10","arxiv_id":"2105.04714","n_code_links":8,"syntology":{"ran":3,"of":7,"unverified":4,"pointer_only":0}}],"papers_shown":1,"tasks":[{"task":"/task/face-detection","name":"Face Detection","papers":1}],"tasks_shown":1,"n_tasks":1,"usage_by_year":[{"year":"2021","papers":1}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/sample-redistribution"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}