Rotated object detection. Strong baseline and State of the art The toolbox ...

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  1. Rotated object detection. Strong baseline and State of the art The toolbox provides strong baselines and state-of-the-art methods in rotated object detection. 39 percent (depending on the number of provided samples) while maintaining its real-time efficiency. 4 days ago · Novelty First application of Fourier rotation equivariance for orientation estimation and feature alignment in oriented object detection, offering a simple, effective, and modular solution that outperforms existing spatial‑only methods. 7 percent, and improves upon the non interactive RTDETR by 7. 6+. Firstly, by employing phase-shift encoding for angle precision, this method uses cosine functions of varying phases and frequencies to replace traditional CSL discontinuous encoding, thus enabling Introduction Recently, object detection in aerial images has gained much attention in computer vision. An analysis of the baselines shows that regular orthogonal bounding boxes are unsuitable for objects which are long, small, and potentially rotated, such as ties and beams, which demonstrates the need for detection algorithms that naturally incorporate object angles. In this sce-nario, the oriented directions of objects vary consider-ably across different images, while multiple orientations of objects exist within an image. Feb 24, 2026 · AbstractTo achieve precise localization and counting of abnormal-cut tobacco in complex cigarette manufacturing environments with interference and occlusion, this study proposes an enhanced YOLOv5s-based method using rotated bounding boxes for detection OpenMMLab Rotated Object Detection Toolbox and Benchmark - open-mmlab/mmrotate To address the issues of low detection accuracy and high miss rates in remote sensing object detection, this study proposes an improved YOLOv5s_CSL method integrated with attention mechanisms. Oriented object detection (OOD) in remote sensing images (RSIs) remains a challenging work due to an arbitrary orientation of instances. Therefore, the detector requires more parameters to encode the orientation information, which are often highly redundant and inefficient. In oriented object detection from drone imagery, many existing RGB-infrared (RGB-IR) fusion methods derive modality weights from input statistics alone, without regard for downstream detection objectives. 85 to 19. However, the detection of small rotated objects remains a major challenge, limiting advancements in remote sensing object detection. List of degree symbols where used in degrees of arc, degree of hour in geo coordinates, degrees of temperature. 4 days ago · Compared to general object detection, objects in remote sensing, such as ships, airplanes, and vehicles, are often oriented in arbitrary directions [11, 46, 2]. For rotated object detection (ROD), Oriented Bounding Box (OBB), which simultaneously predicts both the class and the orientation of each object [53, 39], is a popular solution. Learning rotation-invariant features is critical in modeling a fixed descriptor for instances with its rotated variants. Official code of the paper "ReDet: A Rotation-Equivariant Detector for Aerial Object Detection" (CVPR 2021) - fooWally/ReDet-Rotation-Equivariant-Detector-for-Aerial-Object-Detection To address these limitations, we propose the Hybrid-Anchor Rotation Detector (HA-RDet), which combines the advantages of both anchor-based and anchor-free schemes for oriented object detection. MMRotate provides three mainstream angle representations to meet different paper settings. Jul 2, 2020 · Try using ODTK to detect rotated objects in your own dataset. Mar 1, 2025 · Accurate object detection in remote sensing images is essential for applications such as environmental monitoring, urban planning, and disaster management. IRTR-DE. Different from objects in natural images, aerial objects are often distributed with arbitrary orientation. Modular Design We decompose the rotated object detection framework into different components, which makes it much easy and flexible to build a new model by combining different modules. Make html degree sign, ascii code, unicode. It is a part of the OpenMMLab project. The master branch works with PyTorch 1. Abstract Rotated object detection aims to identify and locate ob-jects in images with arbitrary orientation. MMRotate is an open-source toolbox for rotated object detection based on PyTorch. . Feb 28, 2025 · In this paper, we propose IRTR-DETR, an Interactive and Real-Time Rotated DEtection TRansformer that extends IRT-DETR to predict rotated bounding boxes. You will find it straightforward to train, validate, operationalize, and serve your model with maximum efficiency on your GPU resources. SGFNet comprises three modules: (1) a 2 days ago · Dynamic Kernel Rotation: Enhancing Rotated Object Detection with Adaptive Convolution 原创 于 2026-03-01 00:28:12 发布 · 214 阅读 For example: motor stop detection, fan stop detection, reciprocating motion object stop detection, and belt and gear rotation detection. Our method outperforms the state of the art in interactive rotated object detection on the Tiny-DOTA dataset by 5. We present SGFNet, a Semantic-Guided Fusion Network that feeds detection-level semantics back into the fusion stage through learned importance masks. oti skp pya dmv vgr nnl phu zww coo edn yyx smu nhz tjt jol