WebNov 21, 2024 · Incorporating information about the surroundings can have a significant impact on successfully determining the class of an object. This is of particular interest when determining the phenotypes of cells, for example, in the context of high-throughput screens. WebFisheyeDet[87]强调了对有用数据集的需要,通过对Pascal VOC数据集应用失真来创建模拟鱼眼数据集[88]。 多边形表示和变形形状匹配有助于FisheyeDet,论文提出了无先验鱼眼表示法(NPFRM)来提取自适应失真特征,而不使用透镜图案和校准图案。
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WebFisheyeDet. The No-prior Fisheye Representation Method is proposed to guarantee that the network adaptively extracts distortion features without prior information such as prespecified lens parameters, special calibration patterns, etc. Furthermore, in order to tightly and robustly localize objects in fisheye images, the Distortion Shape ... WebTo address this problem, we propose a self-study and contour-based object detector in fisheye images, named FisheyeDet. The No-prior Fisheye Representation Method is proposed to guarantee that the network adaptively extracts distortion features without prior information such as prespecified lens parameters, special calibration patterns, etc. high heel boots for little girls
[PDF] FisheyeDet: A Self-Study and Contour-Based Object …
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