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  • GitHub - WangXueyang-uestc ARConv: Official repo for Adaptive . . .
    To overcome these limitations, we introduce an innovative convolutional module, Adaptive Rectangular Convolution (ARConv) ARConv adaptively learns both the height and width of the convolutional kernel and dynamically adjusts the number of sampling points based on the learned scale
  • CVPR 2025 Open Access Repository
    To overcome these limitations, we introduce an innovative convolutional module, Adaptive Rectangular Convolution (ARConv) ARConv adaptively learns both the height and width of the convolutional kernel and dynamically adjusts the number of sampling points based on the learned scale
  • Adaptive Rectangular Convolution for Remote Sensing Pansharpening
    ARConv is proposed as a module that can adaptively adjust the sampling positions and change the number of sampling points, enabling it to effectively capture scale-specific features of various objects in remote sensing images
  • CVPR 2025 自适应矩形卷积模块，即插即用-CSDN博客
    在编码器和解码器的各个层中，ARNet用自适应矩形卷积（ARConv）替代了标准卷积，形成了自定义的AR-ResBlock模块，使网络具备根据图像中不同目标尺度自适应调整卷积核形状和采样点数量的能力。
  • ARConv - GitCode
    This approach enables ARConv to effectively capture scale-specific features of various objects within an image, optimizing kernel sizes and sampling locations Additionally, we propose ARNet, a network architecture in which ARConv is the primary convolutional module
  • ARConv README. md at main · WangXueyang-uestc ARConv · GitHub
    To overcome these limitations, we introduce an innovative convolutional module, Adaptive Rectangular Convolution (ARConv) ARConv adaptively learns both the height and width of the convolutional kernel and dynamically adjusts the number of sampling points based on the learned scale
  • ARConv论文解析：ICCV顶会｜用于旋转物体检测的自适应旋转卷积，Adaptive Rotated Convolution for . . .
    该论文提出了一种用于旋转目标检测的自适应旋转卷积模块 ARConv。 论文信息：Adaptive Rotated Convolution for Rotated Object Detection 论文链接： arxiv org pdf 2303 0782 一 ARConv论文理论部分解析 旋转目标检测旨在识别和定位图像中任意方向的物体，近年来成为新兴研究课题。 在场景文本检测、面部检测、航空图像识别以及具身人工智能任务中，物体常以任意方向出现，这给检测算法带来巨大挑战。 尽管旋转目标检测在物体表示、损失函数、感兴趣区域提取和标签分配策略等方面取得进展，但在骨干特征提取器设计上关注较少。 标准骨干网络在处理旋转物体时存在局限性，因其卷积核参数固定，难以适应物体方向的变化。
  • Adaptive Rectangular Convolution for Remote Sensing Pansharpening
    To overcome these limitations, we introduce an innovative convolutional module, Adaptive Rectangular Convolution (ARConv) ARConv adaptively learns both the height and width of the convolutional ker- nel and dynamically adjusts the number of sampling points based on the learned scale


















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