From the 1 of 8 linked papers with an AI index.
8 papers
Volumetric Inverse Rendering via Neural Radiative Transfer
Ntumba Elie Nsampi, Adarsh Djeacoumar, Hans-Peter Seidel +2
The paper introduces a method that uses neural fields to jointly estimate the spatially varying optical properties of participating media and the full light field from multi‑view i…
Forget Superresolution, Sample Adaptively (when Path Tracing)
Martin Bálint, Corentin Salaün, Hans-Peter Seidel +1
Real-time path tracing increasingly operates under extremely low sampling budgets, often below one sample per pixel, as rendering complexity, resolution, and frame-rate requirement…
Jump Restore Light Transport
Sascha Holl, Gurprit Singh, Hans-Peter Seidel
Markov chain Monte Carlo (MCMC) algorithms are indispensable when sampling from a complex, high-dimensional distribution by a conventional method is intractable. Even though MCMC i…
Learning Neural Antiderivatives
Fizza Rubab, Ntumba Elie Nsampi, Martin Balint +4
Neural fields offer continuous, learnable representations that extend beyond traditional discrete formats in visual computing. We study the problem of learning neural representatio…
MILO: A Lightweight Perceptual Quality Metric for Image and Latent-Space Optimization
UÄur ÃoÄalan, Mojtaba Bemana, Karol Myszkowski +2
We present MILO (Metric for Image- and Latent-space Optimization), a lightweight, multiscale, perceptual metric for full-reference image quality assessment (FR-IQA). MILO is traine…
Bracket Diffusion: HDR Image Generation by Consistent LDR Denoising
Mojtaba Bemana, Thomas Leimkühler, Karol Myszkowski +2
We demonstrate generating HDR images using the concerted action of multiple black-box, pre-trained LDR image diffusion models. Relying on a pre-trained LDR generative diffusion mod…