Deep Learning for Visual Computing

Deep Learning for Visual Computing

A Geometry-Sensitive Approach for Photographic Style Classification

A Geometry-Sensitive Approach for Photographic Style Classification

Abstract Photographs are characterized by different compositional attributes like the Rule of Thirds, depth of field, vanishing-lines etc. The presence or absence of one or more of these attributes contributes ...
Read More
AlphaGAN: Generative adversarial networks for natural image matting

AlphaGAN: Generative adversarial networks for natural image matting

Abstract We present the first generative adversarial network (GAN) for natural image matting. Our novel generator network is trained to predict visually appealing alphas with the addition of the adversarial ...
Read More
Deep Normal Estimation for Automatic Shading of Hand-Drawn Characters

Deep Normal Estimation for Automatic Shading of Hand-Drawn Characters

In this paper (Pre-Print) we present a new fully automatic pipeline for generating shading effects on hand-drawn characters. Our method takes as input a single digitized sketch of any resolution ...
Read More
DeepStereoBrush: Interactive Depth Map Creation

DeepStereoBrush: Interactive Depth Map Creation

In this paper, we introduce a novel interactive depth map creation approach for image sequences which uses depth scribbles as input at user-defined keyframes. These scribbled depth values are then ...
Read More
Egocentric Gesture Recognition for Head-Mounted AR devices

Egocentric Gesture Recognition for Head-Mounted AR devices

Natural interaction with virtual objects in AR/VR environments makes for a smooth user experience. Gestures are a natural extension from real world to augmented space to achieve these interactions. Finding ...
Read More
SalNet360: Saliency Maps for omni-directional images with CNN

SalNet360: Saliency Maps for omni-directional images with CNN

Abstract The prediction of Visual Attention data from any kind of media is of valuable use to content creators and used to efficiently drive encoding algorithms. With the current trend ...
Read More