Related papers: UFig v1: The ultra-fast image generator
Spatial frequency domain imaging (SFDI) is a low-cost imaging technique that can deliver real-time maps of absorption and reduced scattering coefficients. However, there are a wide range of imaging geometries that practical SFDI systems…
Recent advancements in AI-based multimedia generation have enabled the creation of hyper-realistic images and videos, raising concerns about their potential use in spreading misinformation. The widespread accessibility of generative…
While diffusion models significantly improve the perceptual quality of super-resolved images, they usually require a large number of sampling steps, resulting in high computational costs and long inference times. Recent efforts have…
To advance research in learning-based defogging algorithms, various synthetic fog datasets have been developed. However, existing datasets created using the Atmospheric Scattering Model (ASM) or real-time rendering engines often struggle to…
Today's deep high resolution multiwavelength surveys contain a wealth of information about galaxies at different epochs. To fully exploit this information, it is useful to be able to produce highly realistic simulations to compare with the…
Recovering the geometry and materials of objects from a single image is challenging due to its under-constrained nature. In this paper, we present Neural LightRig, a novel framework that boosts intrinsic estimation by leveraging auxiliary…
We present redshift-zero synthetic observational data considering dust attenuation and dust emission for the thirty galaxies of the Auriga project, calculated with the SKIRT radiative transfer code. The post-processing procedure includes…
We present allesfitter, a public and open-source python software for flexible and robust inference of stars and exoplanets given photometric and radial velocity data. Allesfitter offers a rich selection of orbital and transit/eclipse…
Hydrodynamical simulations are increasingly able to accurately model physical systems on stellar, galactic, and cosmological scales, however, the utility of these simulations is often limited by our ability to directly compare them with the…
Diffusion models have achieved impressive performance in video generation, but their iterative denoising process remains computationally expensive due to the large number of tokens processed at each timestep. Recently, progressive…
In this paper we propose a mask-conditional synthetic image generation model for creating synthetic satellite imagery datasets. Given a dataset of real high-resolution images and accompanying land cover masks, we show that it is possible to…
Image simulations are essential tools for preparing and validating the analysis of current and future wide-field optical surveys. However, the galaxy models used as the basis for these simulations are typically limited to simple parametric…
Ultra-faint dwarf galaxies, which can be detected as resolved satellite systems of the Milky Way, are critical to understanding galaxy formation, evolution, and the nature of dark matter, as they are the oldest, smallest, most metal-poor,…
In recent years, there have been several advancements in the task of image super-resolution using the state of the art Deep Learning-based architectures. Many super-resolution-based techniques previously published, require high-end and…
The latest generation of radio astronomy interferometers will conduct all sky surveys with data products consisting of petabytes of spectral line data. Traditional approaches to identifying and parameterising the astrophysical sources…
Diffusion models have achieved state-of-the-art results on many modalities including images, speech, and video. However, existing models are not tailored to support remote sensing data, which is widely used in important applications…
The most direct way to confront observed galaxies with those formed in numerical simulations is to forward-model simulated galaxies into synthetic observations. Provided that synthetic galaxy observations include similar constraints and…
We present 'Pix2Prof', a deep learning model that can eliminate any manual steps taken when extracting galaxy profiles. We argue that a galaxy profile of any sort is conceptually similar to a natural language image caption. This idea allows…
$\textbf{scqubits}$ is an open-source Python package for simulating and analyzing superconducting circuits. It provides convenient routines to obtain energy spectra of common superconducting qubits, such as the transmon, fluxonium, flux,…
In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\times$4k pixels) is hindered by the excessive…