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.
圖片來源: Kreateable官網
Kreateable是一個多功能生成AI網站，可以生成logo、廣告、貼文、去背修圖等圖像生成與處理。
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圖片來源: Leap Touch官網
Leap Touch 是一款為用戶提供輕鬆生成和編輯照片的AI工具，通過輸入文字，在幾秒鐘內轉換圖像並生成定製照片。
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圖片來源: Designs.AI官網
Designs.AI利用AI技術，讓您可以快速的建立和編輯您想要的內容。 使用我們的AI引擎來產生您的品牌，並具有獨特的LOGO和完整的品牌套件包，您可以從超過1萬個圖中做選擇。 以JPEG、PDF、PNG或SVG的格式匯出您的LOGO。
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