4 citations · 14 across the 6 of their papers we have counts for
4 papers · 1 filter
Learning multi-scale local conditional probability models of images
Zahra Kadkhodaie, Florentin Guth, Stéphane Mallat +1
Deep neural networks can learn powerful prior probability models for images, as evidenced by the high-quality generations obtained with recent score-based diffusion methods. But th…
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations
Thomas Yerxa, Yilun Kuang, Eero Simoncelli +1
The efficient coding hypothesis proposes that the response properties of sensory systems are adapted to the statistics of their inputs such that they capture maximal information ab…
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…
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…