Latent Sharp Image

Latent sharp image recovery focuses on reconstructing high-quality, clear images from degraded inputs like blurry images or videos, often incorporating information from other sources such as event streams. Current research emphasizes the use of neural radiance fields (NeRFs) and deep learning architectures, including convolutional neural networks and transformers, to model and disentangle the degradation from the underlying sharp image. These advancements are significant for improving image and video quality in various applications, such as high-speed photography, video enhancement, and computationally efficient image compression.