Search Results for author: Terrance DeVries

Found 13 papers, 8 papers with code

Unconstrained Scene Generation with Locally Conditioned Radiance Fields

1 code implementation ICCV 2021 Terrance DeVries, Miguel Angel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind

In this paper, we introduce Generative Scene Networks (GSN), which learns to decompose scenes into a collection of many local radiance fields that can be rendered from a free moving camera.

Scene Generation

Building LEGO Using Deep Generative Models of Graphs

1 code implementation21 Dec 2020 Rylee Thompson, Elahe Ghalebi, Terrance DeVries, Graham W. Taylor

Generative models are now used to create a variety of high-quality digital artifacts.

Instance Selection for GANs

1 code implementation NeurIPS 2020 Terrance DeVries, Michal Drozdzal, Graham W. Taylor

By refining the empirical data distribution before training, we redirect model capacity towards high-density regions, which ultimately improves sample fidelity, lowers model capacity requirements, and significantly reduces training time.

Conditional Image Generation

ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis

1 code implementation ECCV 2020 Eu Wern Teh, Terrance DeVries, Graham W. Taylor

Additionally, our proposed fast moving proxies also addresses small gradient issue of proxies, and this component synergizes well with low temperature scaling and Global Max Pooling.

Image Retrieval Metric Learning

On the Evaluation of Conditional GANs

1 code implementation11 Jul 2019 Terrance DeVries, Adriana Romero, Luis Pineda, Graham W. Taylor, Michal Drozdzal

We show that FJD can be used as a promising single metric for cGAN benchmarking and model selection.

Model Selection

Does Object Recognition Work for Everyone?

no code implementations6 Jun 2019 Terrance DeVries, Ishan Misra, Changhan Wang, Laurens van der Maaten

The paper analyzes the accuracy of publicly available object-recognition systems on a geographically diverse dataset.

Object Recognition

Leveraging Uncertainty Estimates for Predicting Segmentation Quality

no code implementations2 Jul 2018 Terrance DeVries, Graham W. Taylor

The first is producing spatial uncertainty maps, from which a clinician can observe where and why a system thinks it is failing.

Learning Confidence for Out-of-Distribution Detection in Neural Networks

2 code implementations13 Feb 2018 Terrance DeVries, Graham W. Taylor

Modern neural networks are very powerful predictive models, but they are often incapable of recognizing when their predictions may be wrong.

Out-of-Distribution Detection

Improved Regularization of Convolutional Neural Networks with Cutout

24 code implementations15 Aug 2017 Terrance DeVries, Graham W. Taylor

Convolutional neural networks are capable of learning powerful representational spaces, which are necessary for tackling complex learning tasks.

Domain Generalization Image Augmentation +1

Skin Lesion Classification Using Deep Multi-scale Convolutional Neural Networks

no code implementations4 Mar 2017 Terrance DeVries, Dhanesh Ramachandram

We present a deep learning approach to the ISIC 2017 Skin Lesion Classification Challenge using a multi-scale convolutional neural network.

Classification General Classification +2

Dataset Augmentation in Feature Space

1 code implementation17 Feb 2017 Terrance DeVries, Graham W. Taylor

Our main insight is to perform the transformation not in input space, but in a learned feature space.

Unsupervised Representation Learning

Cannot find the paper you are looking for? You can Submit a new open access paper.