… class-specific prior within our deblurring framework. In Figure 3, we compare the visual quality
of the recovered latent image … As observed, the image recovered with the prior does not …

… for image deblurring from a classical image processing perspective. We also compare a
classagnostic and a class-specific … Recently, class-specific information has been employed up to …

… Conventional Single image deblurring: We compare with the state-of-theart conventional …
compared with the dynamic deblurring network of [27] and classspecific deblurring work of [12]. …

… In addition to a class-specific image prior, we consider different priors on the blurring filter.
Earlier methods typically impose constraint for the, arguably, most relevant type of generic …

… In this paper, we propose an unsupervised domainspecific image deblurring method based
on disentangled representations. More specifically, we disentangle the content and blur …

… approach ie progressively restoring a clean image from its low-resolution versions has
been successfully employed for single image deblurring. However, a major disadvantage of …

… [2] propose a new class specific prior which is based on a sub set of band passed filter
responses, whose intensity distributions act as a useful prior to recover the necessary …

… As such, the proposed algorithms can be applied to class specific image deblurring with
fewer constraints. Convolutional Neural Networks. Convolutional neural networks have been …

… In recent years, single image deblurring issue has made significant progress. In this section,
we focus on generic image deblurring methods and face class-specific image deblurring …

… NNs and four optimization techniques for blind deblurring (BD). To do this … Image deblurring
can be achieved by an inversion in the frequency domain to recover the latent sharp image …