168 citations · 233 across the 12 of their papers we have counts for
17 papers
Realistic Saliency Guided Image Enhancement
S. Mahdi H. Miangoleh, Zoya Bylinskii, Eric Kee +2
Common editing operations performed by professional photographers include the cleanup operations: de-emphasizing distracting elements and enhancing subjects. These edits are challe…
THERIF: A Pipeline for Generating Themes for Readability with Iterative Feedback
Tianyuan Cai, Aleena Gertrudes Niklaus, Michael Kraley +2
Digital reading applications give readers the ability to customize fonts, sizes, and spacings, all of which have been shown to improve the reading experience for readers from diffe…
Towards Better User Studies in Computer Graphics and Vision
Zoya Bylinskii, Laura Herman, Aaron Hertzmann +2
Online crowdsourcing platforms have made it increasingly easy to perform evaluations of algorithm outputs with survey questions like "which image is better, A or B?", leading to th…
Readability Research: An Interdisciplinary Approach
Sofie Beier, Sam Berlow, Esat Boucaud +25
Readability is on the cusp of a revolution. Fixed text is becoming fluid as a proliferation of digital reading devices rewrite what a document can do. As past constraints make way…
Mitigating the Effects of Reading Interruptions by Providing Reviews and Previews
Namrata Srivastava, Rajiv Jain, Jennifer Healey +2
As reading on mobile devices is becoming more ubiquitous, content is consumed in shorter intervals and is punctuated by frequent interruptions. In this work, we explore the best wa…
Memorability: An image-computable measure of information utility
Zoya Bylinskii, Lore Goetschalckx, Anelise Newman +1
The pixels in an image, and the objects, scenes, and actions that they compose, determine whether an image will be memorable or forgettable. While memorability varies by image, it…
Toward Quantifying Ambiguities in Artistic Images
Xi Wang, Zoya Bylinskii, Aaron Hertzmann +1
It has long been hypothesized that perceptual ambiguities play an important role in aesthetic experience: a work with some ambiguity engages a viewer more than one that does not. H…
Look here! A parametric learning based approach to redirect visual attention
Youssef Alami Mejjati, Celso F. Gomez, Kwang In Kim +2
Across photography, marketing, and website design, being able to direct the viewer's attention is a powerful tool. Motivated by professional workflows, we introduce an automatic me…
Predicting Visual Importance Across Graphic Design Types
Camilo Fosco, Vincent Casser, Amish Kumar Bedi +3
This paper introduces a Unified Model of Saliency and Importance (UMSI), which learns to predict visual importance in input graphic designs, and saliency in natural images, along w…
Using Behavioral Interactions from a Mobile Device to Classify the Reader's Prior Familiarity and Goal Conditions
Sungjin Nam, Zoya Bylinskii, Christopher Tensmeyer +3
A student reads a textbook to learn a new topic; an attorney leafs through familiar legal documents. Each reader may have a different goal for, and prior knowledge of, their readin…
TurkEyes: A Web-Based Toolbox for Crowdsourcing Attention Data
Anelise Newman, Barry McNamara, Camilo Fosco +5
Eye movements provide insight into what parts of an image a viewer finds most salient, interesting, or relevant to the task at hand. Unfortunately, eye tracking data, a commonly-us…
Bottom-up Attention, Models of
Ali Borji, Hamed R. Tavakoli, Zoya Bylinskii
In this review, we examine the recent progress in saliency prediction and proposed several avenues for future research. In spite of tremendous efforts and huge progress, there is s…
Synthetically Trained Icon Proposals for Parsing and Summarizing Infographics
Spandan Madan, Zoya Bylinskii, Matthew Tancik +6
Widely used in news, business, and educational media, infographics are handcrafted to effectively communicate messages about complex and often abstract topics including `ways to co…
Understanding Infographics through Textual and Visual Tag Prediction
Zoya Bylinskii, Sami Alsheikh, Spandan Madan +5
We introduce the problem of visual hashtag discovery for infographics: extracting visual elements from an infographic that are diagnostic of its topic. Given an infographic as inpu…
Learning Visual Importance for Graphic Designs and Data Visualizations
Zoya Bylinskii, Nam Wook Kim, Peter O'Donovan +6
Knowing where people look and click on visual designs can provide clues about how the designs are perceived, and where the most important or relevant content lies. The most importa…
What do different evaluation metrics tell us about saliency models?
Zoya Bylinskii, Tilke Judd, Aude Oliva +2
How best to evaluate a saliency model's ability to predict where humans look in images is an open research question. The choice of evaluation metric depends on how saliency is defi…
Are all training examples equally valuable?
Agata Lapedriza, Hamed Pirsiavash, Zoya Bylinskii +1
When learning a new concept, not all training examples may prove equally useful for training: some may have higher or lower training value than others. The goal of this paper is to…