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Found 5 papers, 4 papers with code
Learn, Imagine and Create: Text-to-Image Generation from Prior Knowledge
Given a text description, we immediately imagine an overall visual impression using this prior and, based on this, we draw a picture by progressively adding more and more details.
MirrorGAN: Learning Text-to-image Generation by Redescription
Generating an image from a given text description has two goals: visual realism and semantic consistency.
Ranked #8 on
Text-to-Image Generation
on CUB
(Inception score metric)
Ancient Painting to Natural Image: A New Solution for Painting Processing
By doing so, the ancient painting processing problems become natural image processing problems and models trained on natural images can be directly applied to the transferred paintings.
Exploring Human-like Attention Supervision in Visual Question Answering
Since there is a lack of human attention data, we first propose a Human Attention Network (HAN) to generate human-like attention maps, training on a recently released dataset called Human ATtention Dataset (VQA-HAT).
Cross-Media Similarity Evaluation for Web Image Retrieval in the Wild
To quantify the current progress, we propose a simple text2image method, representing a novel test query by a set of images selected from large-scale query log.
