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InfoResearchPeer-reviewed
Toward Better De-Raining Generalization via Rainy Characteristics Memorization and Replay
- Published
- Record updated
Summary
This paper proposes a continual learning framework for image de-raining that lets networks accumulate knowledge from a growing pool of datasets. It uses GANs to capture features of new data, trains the de-raining network on existing and GAN-synthesized data with knowledge distillation, and reports that it works across six datasets and beats state-of-the-art methods on new real-world scenes when tested on three benchmark networks.