{"repo":"YXB-NKU/Strip-R-CNN","free":true,"listed":false,"github":"https://github.com/YXB-NKU/Strip-R-CNN","clone":"git clone https://github.com/YXB-NKU/Strip-R-CNN.git","description":"[AAAI 2026]\"Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection\"","language":"Python","stars":141,"topics":["object-detection","oriented-object-detection","remote-sensing","stripe"],"license":null,"category":"auth-billing-email","readme_excerpt":"Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection Xinbin Yuan , ZhaoHui Zheng , Yuxuan Li , Xialei Liu , Li Liu , Xiang Li , Qibin Hou , Ming-Ming Cheng 博客 If you find our work helpful, please consider giving us a ⭐! Offical implementation of \"Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection\" we also add our config in https://github.com/zcablii/LSKNet Abstract While witnessed with rapid development, remote sensing object detection remains challenging for detecting high aspect ratio objects. This paper shows that large strip convolutions are good feature representation learners for remote sensing object detection and can detect objects of various aspect ratios well. Based on large strip convolutions, we build a new network architecture called Strip R-CNN, which is simple, efficient, and powerful. Unlike recent remote sensing object detectors that leverage large-kernel convolutions with square shapes, our Strip R-CNN takes advantage of sequential orthogonal large strip convolutions to capture spatial information. In addition, we enhance the localization capability of remote-sensing object detectors by decoupling the detection heads and equipping the localization head with strip convolutions to better localize the target objects. Extensive experiments on several benchmarks, for example DOTA, FAIR1M, HRSC2016, and DIOR, show that our Strip R-CNN can greatly improve previous work. In particular, our 30M model achieves 82.75\\% mAP on D","default_branch":null,"files":null,"tree":[],"storefront":"/r/YXB-NKU","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/YXB-NKU/Strip-R-CNN/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}