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FPN对高层特征图采用的放大方式是插值，而UNet通常还会使用转置卷积，通过网络自学习的方式来进行上采样； FPN的高层特征放大2倍后与低层的尺寸恰好一致，而在UNet中通常不一致，还需要对低层特征做crop使得与放大后的高层特征尺寸一致；

fpn这种结构的优点是能把浅层的信息，特别是边缘信息传递过来。 如果你换一个角度看FPN，其实就是个hourglass类似沙漏的结构。 Retina Net uses FPN structure.

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这也与 fpn 结构中“深层特征图（尺度小、分辨率低）适合检测大物体，浅层特征图（尺度大、分辨率高）适合检测小物体”的规律相符。 因此根据此公式，只需输入多尺度特征图的层数、单个 proposal 的宽高以及原图输入尺寸，即可求得当前 proposal 应使用哪一 ...

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对于目标检测任务来说fpn已经是标配了，但对于最原始的vit而言，由于没有下采样，所以无法像cnn那样拥有天生的不同分辨率的特征图。 之前的工作如Swin等，是顺着CNN设计的思路在走，把层次化、逐级下采样的特点重新引入到了ViT中，这样做确实取得了成功 ...

2023年5月14日 · But that shouldn't happen every time you visit FPN between system takedowns. I endeavour to be frank and truthful in what I write, show or otherwise present, when I relate my first-hand experiences that are not independently verifiable; and link to third-party content where I can, when I make a claim or refute a statement of fact in a thread.

prompt = '''You are an expert human annotator working for the search engine Bing.com. ##Context##Each webpage that matches a Bing search query has three pieces of information displayed on the result page: the url, the title and the snippet. The snippet usually contains one or two sentences, capturing the main idea of the webpage and encouraging users to visit the link. …