Search Results for author: Max Ehrlich

Found 9 papers, 2 papers with code

The First Principles of Deep Learning and Compression

no code implementations4 Apr 2022 Max Ehrlich

This allows the incredible advances in deep learning to be used for multimedia compression without threatening the ubiquity of the classical methods.

Leveraging Bitstream Metadata for Fast and Accurate Video Compression Correction

no code implementations31 Jan 2022 Max Ehrlich, Jon Barker, Namitha Padmanabhan, Larry Davis, Andrew Tao, Bryan Catanzaro, Abhinav Shrivastava

Video compression is a central feature of the modern internet powering technologies from social media to video conferencing.

Video Compression

A Frequency Perspective of Adversarial Robustness

no code implementations26 Oct 2021 Shishira R Maiya, Max Ehrlich, Vatsal Agarwal, Ser-Nam Lim, Tom Goldstein, Abhinav Shrivastava

Our analysis shows that adversarial examples are neither in high-frequency nor in low-frequency components, but are simply dataset dependent.

Adversarial Robustness

Interpretable Automated Diagnosis of Retinal Disease Using Deep OCT Analysis

no code implementations3 Sep 2021 Evan Wen, Max Ehrlich

In combination with an OCT segmentation model, this allows us to produce quantitative breakdowns of the specific retinal layers the model focused on for later review by an expert.

Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer

no code implementations16 May 2021 Arthita Ghosh, Max Ehrlich, Larry Davis, Rama Chellappa

Urban material recognition in remote sensing imagery is a highly relevant, yet extremely challenging problem due to the difficulty of obtaining human annotations, especially on low resolution satellite images.

Material Recognition Super-Resolution +1

Analyzing and Mitigating JPEG Compression Defects in Deep Learning

no code implementations17 Nov 2020 Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava

We show that there is a significant penalty on common performance metrics for high compression.

Quantization Guided JPEG Artifact Correction

1 code implementation ECCV 2020 Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava

The JPEG image compression algorithm is the most popular method of image compression because of its ability for large compression ratios.

JPEG Artifact Correction Quantization

Deep Residual Learning in the JPEG Transform Domain

1 code implementation ICCV 2019 Max Ehrlich, Larry Davis

We introduce a general method of performing Residual Network inference and learning in the JPEG transform domain that allows the network to consume compressed images as input.

General Classification Image Classification

Action-Affect Classification and Morphing using Multi-Task Representation Learning

no code implementations21 Mar 2016 Timothy J. Shields, Mohamed R. Amer, Max Ehrlich, Amir Tamrakar

We propose a new model that enhances the CRBM model with a factored multi-task component to become Multi-Task Conditional Restricted Boltzmann Machines (MTCRBMs).

Classification General Classification +3

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