174 citations · 296 across the 15 of their papers we have counts for
9 papers · 1 filter
Robust Two-View Geometry Estimation with Implicit Differentiation
Vladislav Pyatov, Iaroslav Koshelev, Stamatis Lefkimmiatis
We present a novel two-view geometry estimation framework which is based on a differentiable robust loss function fitting. We propose to treat the robust fundamental matrix estimat…
NeuSD: Surface Completion with Multi-View Text-to-Image Diffusion
Savva Ignatyev, Daniil Selikhanovych, Oleg Voynov +4
We present a novel method for 3D surface reconstruction from multiple images where only a part of the object of interest is captured. Our approach builds on two recent developments…
Iterative Reweighted Least Squares Networks With Convergence Guarantees for Solving Inverse Imaging Problems
Iaroslav Koshelev, Stamatios Lefkimmiatis
In this work we present a novel optimization strategy for image reconstruction tasks under analysis-based image regularization, which promotes sparse and/or low-rank solutions in s…
Learning Sparse and Low-Rank Priors for Image Recovery via Iterative Reweighted Least Squares Minimization
Stamatios Lefkimmiatis, Iaroslav Koshelev
We introduce a novel optimization algorithm for image recovery under learned sparse and low-rank constraints, which we parameterize as weighted extensions of the -vector…
Iterative Residual CNNs for Burst Photography Applications
Filippos Kokkinos, Stamatios Lefkimmiatis
Modern inexpensive imaging sensors suffer from inherent hardware constraints which often result in captured images of poor quality. Among the most common ways to deal with such lim…
Iterative Joint Image Demosaicking and Denoising using a Residual Denoising Network
Filippos Kokkinos, Stamatios Lefkimmiatis
Modern digital cameras rely on the sequential execution of separate image processing steps to produce realistic images. The first two steps are usually related to denoising and dem…
Deep Image Demosaicking using a Cascade of Convolutional Residual Denoising Networks
Filippos Kokkinos, Stamatios Lefkimmiatis
Demosaicking and denoising are among the most crucial steps of modern digital camera pipelines and their joint treatment is a highly ill-posed inverse problem where at-least two-th…
Universal Denoising Networks : A Novel CNN Architecture for Image Denoising
Stamatios Lefkimmiatis
We design a novel network architecture for learning discriminative image models that are employed to efficiently tackle the problem of grayscale and color image denoising. Based on…
Non-Local Color Image Denoising with Convolutional Neural Networks
Stamatios Lefkimmiatis
We propose a novel deep network architecture for grayscale and color image denoising that is based on a non-local image model. Our motivation for the overall design of the proposed…