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Found 6 papers, 4 papers with code
Solution for the EPO CodeFest on Green Plastics: Hierarchical multi-label classification of patents relating to green plastics using deep learning
We also interpret our models by visualizing the word importance given by the trained model, which indicates the model is capable to extract high-level semantic information of input documents.
S2IGAN: Speech-to-Image Generation via Adversarial Learning
An estimated half of the world's languages do not have a written form, making it impossible for these languages to benefit from any existing text-based technologies.
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).
