3 papers
eess.IV2026
Structured SIR: Efficient and Expressive Importance-Weighted Inference for High-Dimensional Image Registration
Ivor J. A. Simpson, Neill D. F. Campbell
Image registration is an ill-posed dense vision task, where multiple solutions achieve similar loss values, motivating probabilistic inference. Variational inference has previously…
cs.CV2025
Structured Uncertainty Similarity Score (SUSS): Learning a Probabilistic, Interpretable, Perceptual Metric Between Images
Paula Seidler, Neill D. F. Campbell, Ivor J A Simpson
Perceptual similarity scores that align with human vision are critical for both training and evaluating computer vision models. Deep perceptual losses, such as LPIPS, achieve good…
cs.CV2023
The Robust Semantic Segmentation UNCV2023 Challenge Results
Xuanlong Yu, Yi Zuo, Zitao Wang +34
This paper outlines the winning solutions employed in addressing the MUAD uncertainty quantification challenge held at ICCV 2023. The challenge was centered around semantic segment…