OpenRSD: Towards Open-prompts for Object Detection in Remote Sensing Images

• URL: http://arxiv.org/abs/2503.06146v2
• Date: Fri, 21 Mar 2025 06:47:18 GMT
• Title: OpenRSD: Towards Open-prompts for Object Detection in Remote Sensing Images
• Authors: Ziyue Huang, Yongchao Feng, Shuai Yang, Ziqi Liu, Qingjie Liu, Yunhong Wang,
• Abstract summary: We propose OpenRSD, a universal open-prompt RS object detection framework.<n>OpenRSD supports multimodal prompts and integrates multi-task detection heads to balance accuracy and real-time requirements.<n>Compared to YOLO-World, OpenRSD exhibits an 8.7% higher average precision and achieves an inference speed of 20.8 FPS.
• Score: 45.40710102095654
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Remote sensing object detection has made significant progress, but most studies still focus on closed-set detection, limiting generalization across diverse datasets. Open-vocabulary object detection (OVD) provides a solution by leveraging multimodal associations between text prompts and visual features. However, existing OVD methods for remote sensing (RS) images are constrained by small-scale datasets and fail to address the unique challenges of remote sensing interpretation, include oriented object detection and the need for both high precision and real-time performance in diverse scenarios. To tackle these challenges, we propose OpenRSD, a universal open-prompt RS object detection framework. OpenRSD supports multimodal prompts and integrates multi-task detection heads to balance accuracy and real-time requirements. Additionally, we design a multi-stage training pipeline to enhance the generalization of model. Evaluated on seven public datasets, OpenRSD demonstrates superior performance in oriented and horizontal bounding box detection, with real-time inference capabilities suitable for large-scale RS image analysis. Compared to YOLO-World, OpenRSD exhibits an 8.7\% higher average precision and achieves an inference speed of 20.8 FPS. Codes and models will be released.

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