论文标题
深摄影师和增强剂
Deep Photo Cropper and Enhancer
论文作者
论文摘要
本文介绍了一种新型的图像增强问题。与传统的图像增强方法相比，这些方法主要涉及给定照片的像素修改，我们提出的任务是裁剪图像，该图像嵌入了照片中并增强了裁剪图像的质量。我们将提出的方法分为两个深层网络：深色的裁剪器和深度图像增强器。在照片农作物网络中，我们采用空间变压器来提取嵌入式图像。在照片增强器中，我们采用超分辨率来增加嵌入式图像中的像素数量，并减少像素的拉伸和变形的效果。我们使用图像特征和地面真相之间的余弦距离损失，而增强剂的始终方形损失。此外，我们提出了一个新数据集来训练和测试所提出的方法。最后，我们分析了有关定性和定量评估的提出方法。
This paper introduces a new type of image enhancement problem. Compared to traditional image enhancement methods, which mostly deal with pixel-wise modifications of a given photo, our proposed task is to crop an image which is embedded within a photo and enhance the quality of the cropped image. We split our proposed approach into two deep networks: deep photo cropper and deep image enhancer. In the photo cropper network, we employ a spatial transformer to extract the embedded image. In the photo enhancer, we employ super-resolution to increase the number of pixels in the embedded image and reduce the effect of stretching and distortion of pixels. We use cosine distance loss between image features and ground truth for the cropper and the mean square loss for the enhancer. Furthermore, we propose a new dataset to train and test the proposed method. Finally, we analyze the proposed method with respect to qualitative and quantitative evaluations.
