32 Results
October 1, 2018
The effects of natural scene statistics on text readability in additive displays
Human Factors and Ergonomics Society
The minimum contrast needed for optimal text readability with additive displays (e.g. AR devices) will depend on the spatial structure of the background and text. Natural scenes and text follow similar spectral patterns. Therefore, natural scenes can mask low contrast text – making it difficult to read. In a set of experiments, we determine the minimum viable contrast for readability on an additive display.
By: Daryn R. Blanc-Goldhammer, Kevin J. MacKenzie
AR/VR September 8, 2018
DeepWrinkles: Accurate and Realistic Clothing Modeling
European Conference on Computer Vision (ECCV)
We present a novel method to generate accurate and realistic clothing deformation from real data capture. Previous methods for realistic cloth modeling mainly rely on intensive computation of physics-based simulation (with numerous heuristic parameters), while models reconstructed from visual observations typically suffer from lack of geometric details.
By: Zorah Lähner, Daniel Cremers, Tony Tung
Machine Learning September 7, 2018
Recycle-GAN: Unsupervised Video Retargeting
European Conference on Computer Vision (ECCV)
We introduce a data-driven approach for unsupervised video retargeting that translates content from one domain to another while preserving the style native to a domain, i.e., if contents of John Oliver’s speech were to be transferred to Stephen Colbert, then the generated content/speech should be in Stephen Colbert’s style.
By: Aayush Bansal, Shugao Ma, Deva Ramanan, Yaser SheikhAugust 14, 2018
Deep Appearance Models for Face Rendering
ACM SIGGRAPH
We introduce a deep appearance model for rendering the human face. Inspired by Active Appearance Models, we develop a data-driven rendering pipeline that learns a joint representation of facial geometry and appearance from a multiview capture setup.
By: Stephen Lombardi, Jason Saragih, Tomas Simon, Yaser SheikhJuly 29, 2018
Online Optical Marker-based Hand Tracking with Deep Labels
Special Interest Group on Computer Graphics and Interactive Techniques (SIGGRAPH)
We propose a technique that frames the labeling problem as a keypoint regression problem conducive to a solution using convolutional neural networks.
By: Shangchen Han, Beibei Liu, Robert Wang, Yuting Ye, Christopher D. Twigg, Kenrick Kin
Human Computer Interaction & UX July 7, 2018
Reconstructing Scenes with Mirror and Glass Surfaces
ACM SIGGRAPH
We introduce a fully automatic pipeline that allows us to reconstruct the geometry and extent of planar glass and mirror surfaces while being able to distinguish between the two.
By: Thomas Whelan, Michael Goesele, Steven J. Lovegrove, Julian Straub, Simon Green, Richard Szeliski, Steven Butterfield, Shobhit Verma, Richard Newcombe
AR/VR
Computer Vision June 18, 2018
Eye In-Painting with Exemplar Generative Adversarial Networks
Computer Vision and Pattern Recognition (CVPR)
This paper introduces a novel approach to in-painting where the identity of the object to remove or change is preserved and accounted for at inference time: Exemplar GANs (ExGANs). ExGANs are a type of conditional GAN that utilize exemplar information to produce high-quality, personalized in-painting results.
By: Brian Dolhansky, Cristian Canton FerrerJune 18, 2018
Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies
Computer Vision and Pattern Recognition (CVPR)
We present a unified deformation model for the markerless capture of human movement at multiple scales, including facial expressions, body motion, and hand gestures.
By: Hanbyul Joo, Tomas Simon, Yaser Sheikh
AR/VR
Computer Vision June 18, 2018
Audio to Body Dynamics
Computer Vision and Pattern Recognition (CVPR)
We present a method that gets as input an audio of violin or piano playing, and outputs a video of skeleton predictions which are further used to animate an avatar. The key idea is to create an animation of an avatar that moves their hands similarly to how a pianist or violinist would do, just from audio.
By: Eli Shlizerman, Lucio Dery, Hayden Schoen, Ira Kemelmacher Shlizerman
Computational Photography & Intelligent Cameras June 18, 2018
Detail-Preserving Pooling in Deep Networks
Computer Vision and Pattern Recognition (CVPR)
In this paper, we aim to leverage recent results on image downscaling for the purposes of deep learning.
By: Faraz Saeedan, Nicolas Weber, Michael Goesele, Stefan Roth
AR/VR
Facebook AI Research