"AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks." The AttnGAN is set up to interpret different parts of the input sentences and adjust corresponding regions of the image output based on words' relevance — essentially, the AttnGAN text to image generator should have a leg up over other methods because it's doing more interpretive work on the words you feed it. Researchers at Microsoft’s Deep Learning Technology Center recently taught an algorithm to turn text captions into images. 2. Text to Image: Synthesizing an image based on a textual description. [7] Dash, Ayushman, et al. [6] Xu, Tao, et al. "TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network.." arXiv: Computer Vision and Pattern Recognition(2017). This tool converts images like . AttnGAN – Image generation machine. AttnGAN: Fine-Grained Text to Image Generation With Attentional Generative Adversarial Networks: CVPR: code: 7: Learning to Explain: An Information-Theoretic Perspective on Model Interpretation: ICML: code: 7: Banach Wasserstein GAN: NIPS: code: 7: Gradually Updated Neural Networks for Large-Scale Image Recognition: ICML: code: 7 Show and Tell: A Neural Image Caption Generator, 2014. The proposed AttnGAN significantly outperforms the previous state of the art, boosting the best reported inception score by 14.14% on the CUB dataset and 170.25% on the more challenging COCO dataset. The goal of the model is to visualize text-based captions, and the results are as bizarre as you’d expect. 对于生成器Generator() ... AttnGAN: Fine-Grained Text to Image Generationwith Attentional Generative Adversarial Networks 论文解读 weixin_43551972的博客. Computer Vision and Pattern Recognition (2018): 1316-1324. 图文生成(Image Captioning)：给图片生成一段描述。 Show and Tell: A Neural Image Caption Generator, 2014. Image: User snowflake doodles from the Google Blog . In addition, a deep attentional multimodal similarity model is proposed to compute a fine-grained image-text matching loss for training the generator. Building on ideas from these many previous works, we develop a simple and effective approach for text-based image synthesis using a character-level text encoder and class-conditional GAN. 文本生成图片(Text to Image)：基于文本来生成图片。 AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks, 2017. With glitter text generator tool, you can easily use stylized glitter text in any online or offline platform. Image Describing: Generating a textual description of each object in an image. Deep Visual-Semantic Alignments for Generating Image Descriptions, 2015.

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