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Found 7 papers, 2 papers with code
Learning to Emphasize: Dataset and Shared Task Models for Selecting Emphasis in Presentation Slides
We evaluate a range of state-of-the-art models on this novel dataset by organizing a shared task and inviting multiple researchers to model emphasis in this new domain.
SemEval-2020 Task 10: Emphasis Selection for Written Text in Visual Media
In this paper, we present the main findings and compare the results of SemEval-2020 Task 10, Emphasis Selection for Written Text in Visual Media.
Let Me Choose: From Verbal Context to Font Selection
In this paper, we aim to learn associations between visual attributes of fonts and the verbal context of the texts they are typically applied to.
Learning Emphasis Selection for Written Text in Visual Media from Crowd-Sourced Label Distributions
In visual communication, text emphasis is used to increase the comprehension of written text to convey the author{'}s intent.
Learning to Extract Semantic Structure From Documents Using Multimodal Fully Convolutional Neural Networks
We present an end-to-end, multimodal, fully convolutional network for extracting semantic structures from document images.
Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Network
We present an end-to-end, multimodal, fully convolutional network for extracting semantic structures from document images.
