论文标题
多模式图像使用生成对抗网络插入
Multi-Modality Image Inpainting using Generative Adversarial Networks
论文作者
论文摘要
在过去的几年中，深度学习技术，尤其是生成的对抗网络（GAN）已显着改善了图像插图和图像到图像的翻译任务。据我们所知，将图像镶嵌任务与多模式图像到图像转换结合的问题仍然完好无损。在本文中，我们建议一个模型来解决此问题。该模型将在夜间的夜间图像翻译和介入以及有希望的定性和定量结果上进行评估。
Deep learning techniques, especially Generative Adversarial Networks (GANs) have significantly improved image inpainting and image-to-image translation tasks over the past few years. To the best of our knowledge, the problem of combining the image inpainting task with the multi-modality image-to-image translation remains intact. In this paper, we propose a model to address this problem. The model will be evaluated on combined night-to-day image translation and inpainting, along with promising qualitative and quantitative results.
