Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Lefkimmiatis, Stamatios"'
We present GSLoc: a new visual localization method that performs dense camera alignment using 3D Gaussian Splatting as a map representation of the scene. GSLoc backpropagates pose gradients over the rendering pipeline to align the rendered and target
Externí odkaz:
http://arxiv.org/abs/2410.06165
Autor:
Ignatyev, Savva, Selikhanovych, Daniil, Voynov, Oleg, Wang, Yiqun, Wonka, Peter, Lefkimmiatis, Stamatios, Burnaev, Evgeny
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: surface reconstruction using neural radiance fields for the reconstr
Externí odkaz:
http://arxiv.org/abs/2312.04654
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 some learned transform domain. We parameterize such regularizers using
Externí odkaz:
http://arxiv.org/abs/2308.05745
We introduce a novel optimization algorithm for image recovery under learned sparse and low-rank constraints, which we parameterize as weighted extensions of the $\ell_p^p$-vector and $\mathcal S_p^p$ Schatten-matrix quasi-norms for $0\!
Externí odkaz:
http://arxiv.org/abs/2304.10536
In this work, we study the problem of non-blind image deconvolution and propose a novel recurrent network architecture that leads to very competitive restoration results of high image quality. Motivated by the computational efficiency and robustness
Externí odkaz:
http://arxiv.org/abs/2112.05505
Autor:
Francavilla, Matteo Alessandro, Lefkimmiatis, Stamatios, Villena, Jorge F., Polimeridis, Athanasios G.
Purpose: To develop a general framework for Parallel Imaging (PI) with the use of Maxwell regularization for the estimation of the sensitivity maps (SMs) and constrained optimization for the parameter-free image reconstruction. Theory and Methods: Ce
Externí odkaz:
http://arxiv.org/abs/2008.09042
Microscopy is a powerful visualization tool in biology, enabling the study of cells, tissues, and the fundamental biological processes; yet, the observed images typically suffer from blur and background noise. In this work, we propose a unifying fram
Externí odkaz:
http://arxiv.org/abs/1911.10989
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 limitations is to rely on burst photography, which nowadays acts as the b
Externí odkaz:
http://arxiv.org/abs/1811.12197
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 demosaicking where the former aims to reduce noise from the sensor and th
Externí odkaz:
http://arxiv.org/abs/1807.06403
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-thirds of the information are missing and the rest are corrupted by nois
Externí odkaz:
http://arxiv.org/abs/1803.05215