Abstract: Domain adaptive object detection methods for remote sensing images (RSIs) typically rely on large-scale target-domain data and multiepoch offline adaption training. However, the wide ...
Abstract: Traditional object detection models often lose the detailed outline information of the object. To address this problem, we propose the Fourier Series Object Detection (FSD). It encodes the ...
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The DINOv3 codebase includes several task-specific heads for a variety of tasks, including classification, depth estimation, object detection, and semantic segmentation. The initial focus of this ...
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The inherent noisy and sparse characteristics of radar data pose challenges in finding effective representations for 3D object detection. In this paper, we propose RadarDistill, a novel knowledge ...