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Found 4 papers, 1 papers with code
SVNR: Spatially-variant Noise Removal with Denoising Diffusion
Our formulation also accounts for the correlation that exists between the condition image and the samples along the modified diffusion process.
SeaThru-NeRF: Neural Radiance Fields in Scattering Media
Even more excitingly, we can render clear views of these scenes, removing the medium between the camera and the scene and reconstructing the appearance and depth of far objects, which are severely occluded by the medium.
NAN: Noise-Aware NeRFs for Burst-Denoising
Such assumptions are not realistic in the presence of large motion and high levels of noise.
Metalearning Linear Bandits by Prior Update
In this work we prove, in the context of stochastic linear bandits and Gaussian priors, that as long as the prior is sufficiently close to the true prior, the performance of the applied algorithm is close to that of the algorithm that uses the true prior.
