no code implementations • CVPR 2022 • Hao Jiang, Calvin Murdock, Vamsi Krishna Ithapu
We propose a novel end-to-end deep learning approach that is able to give robust voice activity detection and localization results.
Ranked #1 on Active Speaker Localization on EasyCom
no code implementations • 10 Mar 2021 • Calvin Murdock, George Cazenavette, Simon Lucey
In comparison to classical shallow representation learning techniques, deep neural networks have achieved superior performance in nearly every application benchmark.
no code implementations • CVPR 2021 • George Cazenavette, Calvin Murdock, Simon Lucey
Despite their unmatched performance, deep neural networks remain susceptible to targeted attacks by nearly imperceptible levels of adversarial noise.
no code implementations • CVPR 2020 • Calvin Murdock, Simon Lucey
Choosing a deep neural network architecture is a fundamental problem in applications that require balancing performance and parameter efficiency.
1 code implementation • ECCV 2018 • Calvin Murdock, Ming-Fang Chang, Simon Lucey
Despite a lack of theoretical understanding, deep neural networks have achieved unparalleled performance in a wide range of applications.
no code implementations • ICCV 2017 • Calvin Murdock, Fernando De la Torre
However, methods for subspace learning from subspace-valued data have been notably absent due to incompatibilities with standard problem formulations.
no code implementations • CVPR 2017 • Calvin Murdock, Fernando de la Torre
Principal component analysis (PCA) is one of the most versatile tools for unsupervised learning with applications ranging from dimensionality reduction to exploratory data analysis and visualization.
no code implementations • CVPR 2016 • Calvin Murdock, Zhen Li, Howard Zhou, Tom Duerig
Most deep architectures for image classification--even those that are trained to classify a large number of diverse categories--learn shared image representations with a single model.
no code implementations • ICCV 2015 • Calvin Murdock, Nathan Jacobs, Robert Pless
Satellite imagery of cloud cover is extremely important for understanding and predicting weather.
no code implementations • ICCV 2015 • Calvin Murdock, Fernando de la Torre
If weakly-supervised information is available in the form of image-level tags, SCA factorizes a set of images into semantic groups of superpixels.