activity
20242026
collaborators

8 papers

cs.CV2026

Compact Neural Appearance Models for Efficient Gaussian Splatting

Florian Hahlbohm, Jorge Condor, Linus Franke +2

Explicit primitive-based radiance fields such as 3D Gaussian Splatting typically model view-dependent appearance using low-order spherical harmonics (SH). Although efficient to eva…

cs.CV2026

Beyond Spherical Harmonics: Rethinking Appearance Models for Radiance Reconstruction

Ewa Miazga, Jorge Condor, Piotr Didyk

View-dependent appearance modeling remains a challenging problem in novel-view synthesis and reconstruction. Accurately representing complex angular effects often requires substant…

cs.CV2026

Neural Harmonic Textures for High-Quality Primitive Based Neural Reconstruction

Jorge Condor, Nicolas Moenne-Loccoz, Merlin Nimier-David +3

Primitive-based methods such as 3D Gaussian Splatting have recently become the state-of-the-art for novel-view synthesis and related reconstruction tasks. Compared to neural fields…

cs.GR2026

Gabor Fields: Orientation-Selective Level-of-Detail for Volume Rendering

Jorge Condor, Nicolai Hermann, Mehmet Ata Yurtsever +1

Gaussian-based representations have enabled efficient physically-based volume rendering at a fraction of the memory cost of regular, discrete, voxel-based distributions. However, s…

eess.IV2025

Temporal Brightness Management for Immersive Content

Luca Surace, Jorge Condor, Piotr Didyk

Modern virtual reality headsets demand significant computational resources to render high-resolution content in real-time. Therefore, prioritizing power efficiency becomes crucial,…

cs.CV2024

Human Vision Constrained Super-Resolution

Volodymyr Karpenko, Taimoor Tariq, Jorge Condor +1

Modern deep-learning super-resolution (SR) techniques process images and videos independently of the underlying content and viewing conditions. However, the sensitivity of the huma…