activity
20152019
most citedLearning Visual Importance for Graphic Designs and Data Visualizations

168 citations · 295 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2019

Unsupervised cycle-consistent deformation for shape matching

Thibault Groueix, Matthew Fisher, Vladimir G. Kim +2

We propose a self-supervised approach to deep surface deformation. Given a pair of shapes, our algorithm directly predicts a parametric transformation from one shape to the other r…

cs.HC2017168 cited

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…

cs.CV2017

Localizing Moments in Video with Natural Language

Lisa Anne Hendricks, Oliver Wang, Eli Shechtman +3

We consider retrieving a specific temporal segment, or moment, from a video given a natural language text description. Methods designed to retrieve whole video clips with natural l…

cs.CV201793 cited

PixelNet: Representation of the pixels, by the pixels, and for the pixels

Aayush Bansal, Xinlei Chen, Bryan Russell +2

We explore design principles for general pixel-level prediction problems, from low-level edge detection to mid-level surface normal estimation to high-level semantic segmentation.…

cs.CV2016

Marr Revisited: 2D-3D Alignment via Surface Normal Prediction

Aayush Bansal, Bryan Russell, Abhinav Gupta

We introduce an approach that leverages surface normal predictions, along with appearance cues, to retrieve 3D models for objects depicted in 2D still images from a large CAD objec…

cs.CV201534 cited

Understanding deep features with computer-generated imagery

Mathieu Aubry, Bryan Russell

We introduce an approach for analyzing the variation of features generated by convolutional neural networks (CNNs) with respect to scene factors that occur in natural images. Such…