Text‐to‐image synthesis refers to computational methods which translate human written
textual descriptions, in the form of keywords or sentences, into images with similar semantic …

We propose a novel hierarchical approach for text-to-image synthesis by inferring semantic
layout. Instead of learning a direct map** from text to image, our algorithm decomposes …

Cross-modal garment synthesis and manipulation will significantly benefit the way fashion
designers generate garments and modify their designs via flexible linguistic interfaces …

Synthesizing photo-realistic images based on text descriptions is a challenging task in the
field of computer vision. Although generative adversarial networks have made significant …

Generative adversarial networks (GANs) have attained a lot of attention in the deep learning
community and have been in focus for the past few years. GAN finds its application in …

Text has traditionally been used to train automated classifiers for a multitude of purposes,
such as: classification, topic modelling and sentiment analysis. State-of-the-art LSTM …

We describe a new approach that improves the training of generative adversarial nets
(GANs) for synthesizing diverse images from a text input. Our approach is based on the …

Text-to-image generation has attracted significant interest from researchers and practitioners
in recent years due to its widespread and diverse applications across various industries …