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PIP: Positional-encoding Image Prior
March 5, 2024, 2:49 p.m. | Nimrod Shabtay, Eli Schwartz, Raja Giryes
cs.CV updates on arXiv.org arxiv.org
Abstract: In Deep Image Prior (DIP), a Convolutional Neural Network (CNN) is fitted to map a latent space to a degraded (e.g. noisy) image but in the process learns to reconstruct the clean image. This phenomenon is attributed to CNN's internal image-prior. We revisit the DIP framework, examining it from the perspective of a neural implicit representation. Motivated by this perspective, we replace the random or learned latent with Fourier-Features (Positional Encoding). We show that thanks …
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