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由 H Ku 著作 · 2023 · 被引用 16 次 — Text-to-image synthesis refers to the process of producing images from textual descriptions, which presents a formidable challenge as it ...

We introduce GigaGAN, a new GAN architecture that far exceeds this limit, demonstrating GANs as a viable option for text-to-image synthesis. GigaGAN offers ...

由 M Tao 著作 · 2022 · 被引用 199 次 — Synthesizing high-quality realistic images from text de- scriptions is a challenging task. Existing text-to-image Gen-.

Text-to-Image Generation is a task in computer vision and natural language processing where the goal is to generate an image that corresponds to a given ...

由 S Reed 著作 · 被引用 3836 次 — Our model can in many cases generate visually-plausible 64×64 images con- ditioned on text, and is also distinct in that our entire model is a GAN, rather only ...

This is a PyTorch-based implementation of the Generative Adversarial Text-to-Image Synthesis paper, utilizing a GAN architecture inspired by DCGAN with text ...

由 M Kang 著作 · 2023 · 被引用 244 次 — We introduce GigaGAN, a new GAN architecture that far exceeds this limit, demonstrating GANs as a viable option for text-to-image synthesis.

由 W Liao 著作 · 2022 · 被引用 112 次 — Text-to-image synthesis (T2I) aims to generate photo- realistic images which are semantically consistent with the text descriptions.

由 V Talasila 著作 · 2022 · 被引用 8 次 — This research aims to develop a new text-to-image synthesis method that includes the two crucial steps of (i) text to picture encoding and (ii) optimized GAN.

This repository consists of code that is used to convert text-embeddings into Images using Generative Adversarial Networks(GAN) ...