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Found 18 papers, 10 papers with code
Total Disentanglement of Font Images into Style and Character Class Features
Second, it is demonstrated that the disentangled features produced by total disentanglement apply to a variety of tasks, including font recognition, character recognition, and one-shot font image generation.
Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation
We show that a simple retrieval augmentation can significantly improve the generation quality.
Towards Diverse and Consistent Typography Generation
In this work, we consider the typography generation task that aims at producing diverse typographic styling for the given graphic document.
Towards Flexible Multi-modal Document Models
Creative workflows for generating graphical documents involve complex inter-related tasks, such as aligning elements, choosing appropriate fonts, or employing aesthetically harmonious colors.
LayoutDM: Discrete Diffusion Model for Controllable Layout Generation
Controllable layout generation aims at synthesizing plausible arrangement of element bounding boxes with optional constraints, such as type or position of a specific element.
Generative Colorization of Structured Mobile Web Pages
The web page colorization problem is then formalized as a task of estimating plausible color styles for a given web page content with a given hierarchical structure of the elements.
CanvasVAE: Learning to Generate Vector Graphic Documents
In this work, we attempt to learn a generative model of vector graphic documents.
Constrained Graphic Layout Generation via Latent Optimization
We optimize using the latent space of an off-the-shelf layout generation model, allowing our approach to be complementary to and used with existing layout generation models.
Serif or Sans: Visual Font Analytics on Book Covers and Online Advertisements
In this paper, we conduct a large-scale study of font statistics in book covers and online advertisements.
Recommending Outfits from Personal Closet
We consider grading a fashion outfit for recommendation, where we assume that users have a closet of items and we aim at producing a score for an arbitrary combination of items in the closet.
Feedback-prop: Convolutional Neural Network Inference under Partial Evidence
We propose an inference procedure for deep convolutional neural networks (CNNs) when partial evidence is available.
End-to-end learning potentials for structured attribute prediction
We present a structured inference approach in deep neural networks for multiple attribute prediction.
Looking at Outfit to Parse Clothing
This paper extends fully-convolutional neural networks (FCN) for the clothing parsing problem.
Automatic Attribute Discovery with Neural Activations
This paper proposes an automatic approach to discover and analyze visual attributes from a noisy collection of image-text data on the Web.
