Papers Layout Generation
“Layout Generation” 태그가 달린 논문 148편 · 필터 해제
Automatic Layout Generation with Applications in Machine Learning Engine Evaluation
Machine learning-based lithography hotspot detection has been deeply studied recently, from varies feature extraction techniques to efficient learning models. It has been observed that such machine learning-based framewo…
BIG-bench Machine LearningLayout GenerationTriplet-Aware Scene Graph Embeddings
Scene graphs have become an important form of structured knowledge for tasks such as for image generation, visual relation detection, visual question answering, and image retrieval. While visualizing and interpreting wor…
Data AugmentationGraph EmbeddingImage GenerationImage Retrieval+8Relationship-Aware Spatial Perception Fusion for Realistic Scene Layout Generation
The significant progress on Generative Adversarial Networks (GANs) have made it possible to generate surprisingly realistic images for single object based on natural language descriptions. However, controlled generation …
DiversityImage GenerationLayout GenerationObjectREAD: Recursive Autoencoders for Document Layout Generation
Layout is a fundamental component of any graphic design. Creating large varieties of plausible document layouts can be a tedious task, requiring numerous constraints to be satisfied, including local ones relating differe…
Layout GenerationContinuous Graph Flow
In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, …
Density EstimationGraph GenerationLayout GenerationLayoutVAE: Stochastic Scene Layout Generation From a Label Set
Recently there is an increasing interest in scene generation within the research community. However, models used for generating scene layouts from textual description largely ignore plausible visual variations within the…
Layout GenerationScene GenerationLayoutGAN: Generating Graphic Layouts with Wireframe Discriminator
Layouts are important for graphic design and scene generation. We propose a novel generative adversarial network, named as LayoutGAN, that synthesizes graphic layouts by modeling semantic and geometric relations of 2D el…
Generative Adversarial NetworkLayout GenerationScene GenerationLayoutGAN: Generating Graphic Layouts with Wireframe Discriminators
Layout is important for graphic design and scene generation. We propose a novel Generative Adversarial Network, called LayoutGAN, that synthesizes layouts by modeling geometric relations of different types of 2D elements…
Generative Adversarial NetworkLayout GenerationScene Generation