论文标题
crformer：用于删除阴影的跨区域变压器
CRFormer: A Cross-Region Transformer for Shadow Removal
论文作者
论文摘要
旨在恢复图像中阴影区域的原始强度，并使它们与剩余的非阴影区域兼容，而删除阴影是一个非常具有挑战性的问题，有益于许多下游图像/视频相关的任务。最近，变形金刚通过捕获全局像素相互作用来显示它们在各种应用中的强大能力，并且在删除阴影时，这种能力是非常可取的。但是，由于以下两个原因，应用变压器促进阴影去除是不乏味的：1）由于不规则的阴影形状，修补操作不适合去除阴影； 2）阴影去除只需要从非阴影区域到阴影区域的单向交互，而不是图像中所有像素之间的共同双向相互作用。在本文中，我们提出了一种新颖的跨区域变压器，即Crformer，用于删除阴影，它与现有变压器仅通过考虑从非阴影区域到阴影区域的像素相互作用而不将图像分解为斑块而有所不同。这是通过精心设计的区域感知的跨注意操作来实现的，该操作可以汇总以非阴影区域特征为条件的恢复的阴影区域特征。与其他最先进的方法相比，关于ISTD，AISTD，SRD和视频阴影删除数据集的广泛实验证明了我们方法的优势。
Aiming to restore the original intensity of shadow regions in an image and make them compatible with the remaining non-shadow regions without a trace, shadow removal is a very challenging problem that benefits many downstream image/video-related tasks. Recently, transformers have shown their strong capability in various applications by capturing global pixel interactions and this capability is highly desirable in shadow removal. However, applying transformers to promote shadow removal is non-trivial for the following two reasons: 1) The patchify operation is not suitable for shadow removal due to irregular shadow shapes; 2) shadow removal only needs one-way interaction from the non-shadow region to the shadow region instead of the common two-way interactions among all pixels in the image. In this paper, we propose a novel cross-region transformer, namely CRFormer, for shadow removal which differs from existing transformers by only considering the pixel interactions from the non-shadow region to the shadow region without splitting images into patches. This is achieved by a carefully designed region-aware cross-attention operation that can aggregate the recovered shadow region features conditioned on the non-shadow region features. Extensive experiments on ISTD, AISTD, SRD, and Video Shadow Removal datasets demonstrate the superiority of our method compared to other state-of-the-art methods.
