617 citations · 763 across the 16 of their papers we have counts for
19 papers
Beyond Monoscopic Viewing: A Study on 3D Gaussian Splatting Quality in VR
Shreyas Shivakumara, Gabriel Eilertsen, Karljohan Lundin Palmerius
Stereoscopy is fundamental to virtual reality (VR), providing depth perception through binocular viewing. Recent advances in 3D Gaussian Splatting (3DGS) enable high-quality novel…
A Comparative Study of Label-free Representation Quality Metrics in Deep Learning
Daniel Richards Arputharaj, Daniel Jönsson, Gabriel Eilertsen
We present a comparative study of label-free metrics for assessing the quality of representations in deep neural networks to understand their reliability under a wide variety of co…
Exploring Metric Fusion for Evaluation of NeRFs
Shreyas Shivakumara, Gabriel Eilertsen, Karljohan Lundin Palmerius
Neural Radiance Fields (NeRFs) have demonstrated significant potential in synthesizing novel viewpoints. Evaluating the NeRF-generated outputs, however, remains a challenge due to…
Detecting Domain Shift in Multiple Instance Learning for Digital Pathology Using Fréchet Domain Distance
Milda Pocevičiūtė, Gabriel Eilertsen, Stina Garvin +1
Multiple-instance learning (MIL) is an attractive approach for digital pathology applications as it reduces the costs related to data collection and labelling. However, it is not c…
Joint tone mapping and denoising of thermal infrared images via multi-scale Retinex and multi-task learning
Axel Gödrich, Daniel König, Gabriel Eilertsen +1
Cameras digitize real-world scenes as pixel intensity values with a limited value range given by the available bits per pixel (bpp). High Dynamic Range (HDR) cameras capture those…
Standalone Neural ODEs with Sensitivity Analysis
Rym Jaroudi, Lukáš Malý, Gabriel Eilertsen +3
This paper presents the Standalone Neural ODE (sNODE), a continuous-depth neural ODE model capable of describing a full deep neural network. This uses a novel nonlinear conjugate g…