SCST reports the best perceptual quality (LPIPS/DISTS) on four synthetic benchmarks and the best no-reference quality scores on the real-world VideoLQ benchmark by adding spatio-temporal Mamba and contrastive ControlNet to a latent diffusion model.
Masked siamese networks for label-efficient learning
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Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution
SCST reports the best perceptual quality (LPIPS/DISTS) on four synthetic benchmarks and the best no-reference quality scores on the real-world VideoLQ benchmark by adding spatio-temporal Mamba and contrastive ControlNet to a latent diffusion model.