28 citations · 73 across the 5 of their papers we have counts for
6 papers
Deep Implicit Surface Point Prediction Networks
Rahul Venkatesh, Tejan Karmali, Sarthak Sharma +4
Deep neural representations of 3D shapes as implicit functions have been shown to produce high fidelity models surpassing the resolution-memory trade-off faced by the explicit repr…
DUDE: Deep Unsigned Distance Embeddings for Hi-Fidelity Representation of Complex 3D Surfaces
Rahul Venkatesh, Sarthak Sharma, Aurobrata Ghosh +2
High fidelity representation of shapes with arbitrary topology is an important problem for a variety of vision and graphics applications. Owing to their limited resolution, classic…
To Beta or Not To Beta: Information Bottleneck for DigitaL Image Forensics
Aurobrata Ghosh, Zheng Zhong, Steve Cruz +3
We consider an information theoretic approach to address the problem of identifying fake digital images. We propose an innovative method to formulate the issue of localizing manipu…
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement
Ryutaro Tanno, Daniel Worrall, Enrico Kaden +6
Deep learning (DL) has shown great potential in medical image enhancement problems, such as super-resolution or image synthesis. However, to date, little consideration has been giv…
SpliceRadar: A Learned Method For Blind Image Forensics
Aurobrata Ghosh, Zheng Zhong, Terrance E Boult +1
Detection and localization of image manipulations like splices are gaining in importance with the easy accessibility of image editing softwares. While detection generates a verdict…
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
Ryutaro Tanno, Daniel E. Worrall, Aurobrata Ghosh +4
In this work, we investigate the value of uncertainty modeling in 3D super-resolution with convolutional neural networks (CNNs). Deep learning has shown success in a plethora of me…