activity
20232026
most citedMetrics that matter: Evaluating image quality metrics for medical image generation

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

VENI: Variational Encoder for Natural Illumination

Paul Walker, James A. D. Gardner, Andreea Ardelean +2

Inverse rendering is an ill-posed problem, but priors such as illumination priors can help simplify it. Existing work either disregards the spherical and rotation-equivariant natur…

eess.IV2025★ 3 cited

Metrics that matter: Evaluating image quality metrics for medical image generation

Yash Deo, Yan Jia, Toni Lassila +5

Evaluating generative models for synthetic medical imaging is crucial yet challenging, especially given the high standards of fidelity, anatomical accuracy, and safety required for…

cs.LG2025

NeuRaLaTeX: A machine learning library written in pure LaTeX

James A. D. Gardner, Will Rowan, William A. P. Smith

In this paper, we introduce NeuRaLaTeX, which we believe to be the first deep learning library written entirely in LaTeX. As part of your LaTeX document you can specify the archite…

cs.CV2023

RENI++ A Rotation-Equivariant, Scale-Invariant, Natural Illumination Prior

James A. D. Gardner, Bernhard Egger, William A. P. Smith

Inverse rendering is an ill-posed problem. Previous work has sought to resolve this by focussing on priors for object or scene shape or appearance. In this work, we instead focus o…

cs.CV2023

The Sky's the Limit: Re-lightable Outdoor Scenes via a Sky-pixel Constrained Illumination Prior and Outside-In Visibility

James A. D. Gardner, Evgenii Kashin, Bernhard Egger +1

Inverse rendering of outdoor scenes from unconstrained image collections is a challenging task, particularly illumination/albedo ambiguities and occlusion of the illumination envir…