4 papers
Self-Supervised Uncertainty Estimation For Super-Resolution of Satellite Images
Zhe Zheng, Valéry Dewil, Pablo Arias
Super-resolution (SR) of satellite imagery is challenging due to the lack of paired low-/high-resolution data. Recent self-supervised SR methods overcome this limitation by exploit…
Adapting MIMO video restoration networks to low latency constraints
Valéry Dewil, Zhe Zheng, Arnaud Barral +7
MIMO (multiple input, multiple output) approaches are a recent trend in neural network architectures for video restoration problems, where each network evaluation produces multiple…
Self-supervision versus synthetic datasets: which is the lesser evil in the context of video denoising?
Valéry Dewil, Aranud Barral, Gabriele Facciolo +1
Supervised training has led to state-of-the-art results in image and video denoising. However, its application to real data is limited since it requires large datasets of noisy-cle…
Self-Supervised training for blind multi-frame video denoising
Valéry Dewil, Jérémy Anger, Axel Davy +3
We propose a self-supervised approach for training multi-frame video denoising networks. These networks predict frame t from a window of frames around t. Our self-supervised approa…