Object detection in aerial images github. Ideal for aerial image analysis.
Object detection in aerial images github. 0 released with all images and oriented bounding box annotations for training and vallidation! Description DOTA is a large-scale dataset for object detection in aerial images. Our work first categorises the current methods for aerial object detection using deep learning techniques and discusses how the task is different from general object detection scenarios. Updated at 2024-06. A common solution is to divide the large aerial image into small (uniform) crops and then apply object detection on each small crop. Even though object detection has achieved significant progress thanks to the development of deep neural networks, most of them are dedicated to detecting objects of normal size. Experiments were conducted on specially created datasets, DIOR-C and DIOR-Cloudy, derived from the publicly available DIOR dataset. It can be used to develop and evaluate object detectors in aerial images. 🔥 A curated list of awesome resources for generic object detection in aerial images. 7M Oriented Bounding Boxes across 18 categories. May 19, 2025 · Explore the DOTA dataset for object detection in aerial images, featuring 1. osw lhdl hkz y5x3z 5hc q4 1or sciyrj wh2 wlix
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