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Achieve 21x faster training and 11x faster rendering in novel view synthesis from degraded images by jointly tackling enhancement and reconstruction in 3D.
By reinterpreting unsupervised anomaly detection through the lens of Retrieval-Augmented Generation, RAID achieves state-of-the-art performance by using retrieved normal samples to guide noise suppression in anomaly map generation.
