facades_pix2pix

facades_pix2pix数据集是Pix2Pix模型训练的其中一个数据集。Pix2Pix利用成对的图片进行图像翻译，即输入为同一张图片的两种不同风格，可用于进行风格迁移。研究条件对抗网络作为图像到图像转换问题的通用解决方案。这些网络不仅学习从输入图像到输出图像的映射，还学习了一个损失函数来训练这个映射。这使得将相同的通用方法应用于传统上需要非常不同的损失公式的问题成为可能。我们证明了这种方法在从标签图合成照片、从边缘图重建对象以及对图像进行着色等任务方面是有效的。

The facades_pix2pix dataset is one of the datasets used for training the Pix2Pix model. Pix2Pix utilizes paired images for image translation, where the inputs are two different styles of the same image, and can be applied for style transfer. It investigates conditional adversarial networks as a general-purpose solution to image-to-image translation problems. These networks not only learn the mapping from input images to output images, but also learn a loss function to train this mapping. This enables the application of the same general method to problems that traditionally require drastically different loss formulations. We demonstrate the effectiveness of this approach on tasks such as synthesizing photographs from label maps, reconstructing objects from edge maps, and colorizing images.

搜集汇总

背景与挑战

背景概述

facades_pix2pix数据集是用于Pix2Pix模型训练的成对图片数据集，支持图像翻译和风格迁移任务，由University of California, Berkeley于2017年发布。