{"url":"/method/image-scale-augmentation","slug":"image-scale-augmentation","name":"Image Scale Augmentation","full_name":"Image Scale Augmentation","full_name_withheld":false,"description_markdown":"Image Scale Augmentation is an augmentation technique where we randomly pick the short size of a image within a dimension range. One use case of this augmentation technique is in object detectiont asks.","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":null,"title":null,"url_on_a_paper_host":false},"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":9,"archive_num_papers":9,"papers_newest_first":[{"paper":"/paper/cross-database-liveness-detection-insights","title":"Cross-Database Liveness Detection: Insights from Comparative Biometric Analysis","date":"2024-01-29","arxiv_id":"2401.16232","n_code_links":4,"syntology":null},{"paper":"/paper/augstatic-a-light-weight-image-augmentation","title":"AugStatic - A Light-Weight Image Augmentation Library","date":"2022-05-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/improving-model-performance-and-removing-the","title":"Improving Model Performance and Removing the Class Imbalance Problem Using Augmentation","date":"2022-05-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/detectron2-object-detection-manipulating","title":"Detectron2 Object Detection & Manipulating Images using Cartoonization","date":"2021-08-01","arxiv_id":null,"n_code_links":2,"syntology":null},{"paper":"/paper/a-comparative-study-on-efficiencies-of","title":"A Comparative Study on Efficiencies of Variants of Convolutional Neural Networks based on Image Classification Task","date":"2020-10-15","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/spinalnet-deep-neural-network-with-gradual-1","title":"SpinalNet: Deep Neural Network with Gradual Input","date":"2020-07-07","arxiv_id":"2007.03347","n_code_links":3,"syntology":null},{"paper":"/paper/resnest-split-attention-networks","title":"ResNeSt: Split-Attention Networks","date":"2020-04-19","arxiv_id":"2004.08955","n_code_links":36,"syntology":{"ran":8,"of":48,"unverified":40,"pointer_only":23}},{"paper":"/paper/efficientdet-scalable-and-efficient-object","title":"EfficientDet: Scalable and Efficient Object Detection","date":"2019-11-20","arxiv_id":"1911.09070","n_code_links":64,"syntology":{"ran":11,"of":70,"unverified":59,"pointer_only":3}},{"paper":"/paper/learning-data-augmentation-strategies-for","title":"Learning Data Augmentation Strategies for Object Detection","date":"2019-06-26","arxiv_id":"1906.11172","n_code_links":6,"syntology":{"ran":3,"of":3,"unverified":0,"pointer_only":3}}],"papers_shown":9,"tasks":[{"task":"/task/image-classification","name":"Image Classification","papers":7},{"task":"/task/image-augmentation","name":"Image Augmentation","papers":5},{"task":"/task/object-detection","name":"Object Detection","papers":4},{"task":"/task/classification-1","name":"Classification","papers":3},{"task":"/task/data-augmentation","name":"Data Augmentation","papers":3},{"task":"/task/data-visualization","name":"Data Visualization","papers":3},{"task":"/task/image-manipulation","name":"Image Manipulation","papers":3},{"task":"/task/object","name":"Object","papers":3},{"task":"/task/image-classification","name":"image-classification","papers":3},{"task":"/task/detecting-image-manipulation","name":"Detecting Image Manipulation","papers":2},{"task":"/task/image-cropping","name":"Image Cropping","papers":2},{"task":"/task/image-denoising","name":"Image Denoising","papers":2},{"task":"/task/image-generation","name":"Image Generation","papers":2},{"task":"/task/image-manipulation-detection","name":"Image Manipulation Detection","papers":2},{"task":"/task/image-matting","name":"Image Matting","papers":2},{"task":"/task/image-morphing","name":"Image Morphing","papers":2},{"task":"/task/image-stitching","name":"Image Stitching","papers":2},{"task":"/task/image-variation","name":"Image-Variation","papers":2},{"task":"/task/instance-segmentation","name":"Instance Segmentation","papers":2},{"task":"/task/panoptic-segmentation","name":"Panoptic Segmentation","papers":2}],"tasks_shown":20,"n_tasks":36,"usage_by_year":[{"year":"2019","papers":2},{"year":"2020","papers":3},{"year":"2021","papers":1},{"year":"2022","papers":2},{"year":"2024","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/image-scale-augmentation"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}