圖片來源: Image-to-Image Translation with Conditional Adversarial Networks官網
透過特定的圖像資料集來訓練，製作一個自動依據邊緣形狀形成特定內容的圖像生成AI。
應用面：
The paper regarding on this investigation was written in 2016 by four scholars at UC Berkeley where it looks at the use of conditional adversarial network as the solution to image-to-image translation problems. Before going into the application of pix2pix, I want go over a little about what “conditional adversarial nets” is.
Conference: 2017 IEEE Conference on Computer Vision and Pattern Recognition CVPR
By the end of this article, you will have a comprehensive understanding of image-to-image translation with conditional adversarial networks and how to apply it in practice.
This article aims to explain the key ideas behind conditional adversarial networks and provide insights into their implementation and training process.
Image-to-image translation is the controlled conversion of a given source image to a target image. Examples include translating a photograph of a landscape from day to night or translating a segmented image to a photograph, synthesizing photos from label maps, reconstructing objects from edge maps, and colorizing images, among other tasks.
The Pix2Pix Generative Adversarial Network, or GAN, is an approach to training a deep convolutional neural network for image-to-image translation tasks.
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感謝您的建議，我們將廣搜意見後優化分類！
