4 citations · 8 across the 3 of their papers we have counts for
4 papers · 1 filter
Unsupervised Deep Video Denoising
Dev Yashpal Sheth, Sreyas Mohan, Joshua L. Vincent +5
Deep convolutional neural networks (CNNs) for video denoising are typically trained with supervision, assuming the availability of clean videos. However, in many applications, such…
Self-Supervised Learning of a Biologically-Inspired Visual Texture Model
Nikhil Parthasarathy, Eero P. Simoncelli
We develop a model for representing visual texture in a low-dimensional feature space, along with a novel self-supervised learning objective that is used to train it on an unlabele…
Comparison of Image Quality Models for Optimization of Image Processing Systems
Keyan Ding, Kede Ma, Shiqi Wang +1
The performance of objective image quality assessment (IQA) models has been evaluated primarily by comparing model predictions to human quality judgments. Perceptual datasets gathe…
Image Quality Assessment: Unifying Structure and Texture Similarity
Keyan Ding, Kede Ma, Shiqi Wang +1
Objective measures of image quality generally operate by comparing pixels of a "degraded" image to those of the original. Relative to human observers, these measures are overly sen…