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Peter Crozier

2 accepted papers

2023

Evaluating Unsupervised Denoising Requires Unsupervised Metrics

ICML 2023poster

Unsupervised denoising is a crucial challenge in real-world imaging applications. Unsupervised deep-learning methods have demonstrated impressive performance on benchmarks based on synthetic noise. However, no metrics exist to evaluate these methods in an unsupervised fashion. This is highly problem…

2021

Adaptive Denoising via GainTuning

NeurIPS 2021poster

Deep convolutional neural networks (CNNs) for image denoising are typically trained on large datasets. These models achieve the current state of the art, but they do not generalize well to data that deviate from the training distribution. Recent work has shown that it is possible to train denoisers…

Cited by 34SourcePDFScholar