17 citations · 20 across the 10 of their papers we have counts for
11 papers
Shedding Light: A Benchmark for Evaluating Lighting Understanding in Generative Image Models
Justine Giroux, Jack Oliver Hilliard, Yannick Hold-Geoffroy +2
Accurate modelling of illumination is central to realistic image synthesis and scene understanding. Yet, there is little exploration into whether image generative models are good a…
GRay: Ray Tracing 3D Gaussians Near the Speed of Splats
Yohan Poirier-Ginter, Jean-François Lalonde, George Drettakis
3D Gaussian Splatting (3DGS) is a popular representation for radiance field reconstruction, distinguished by the rendering speed of its rasterization-based renderer. While 3D Gauss…
Editable Physically-based Reflections in Raytraced Gaussian Radiance Fields
Yohan Poirier-Ginter, Jeffrey Hu, Jean-François Lalonde +1
Radiance fields such as 3D Gaussian Splatting allow real-time rendering of scenes captured from photos. They also reconstruct most specular reflections with high visual quality, bu…
Lighting in Motion: Spatiotemporal HDR Lighting Estimation
Christophe Bolduc, Julien Philip, Li Ma +3
We present Lighting in Motion (LiMo), a diffusion-based approach to spatiotemporal lighting estimation. LiMo targets both realistic high-frequency detail prediction and accurate il…
GimbalDiffusion: Gravity-Aware Camera Control for Video Generation
Frédéric Fortier-Chouinard, Yannick Hold-Geoffroy, Valentin Deschaintre +2
Recent progress in text-to-video generation has achieved remarkable realism, yet fine-grained control over camera motion and orientation remains elusive, especially with extreme tr…
Improving the color accuracy of lighting estimation models
Zitian Zhang, Joshua Urban Davis, Jeanne Phuong Anh Vu +2
Advances in high dynamic range (HDR) lighting estimation from a single image have opened new possibilities for augmented reality (AR) applications. Predicting complex lighting envi…
Material Transforms from Disentangled NeRF Representations
Ivan Lopes, Jean-François Lalonde, Raoul de Charette
In this paper, we first propose a novel method for transferring material transformations across different scenes. Building on disentangled Neural Radiance Field (NeRF) representati…
ZeroComp: Zero-shot Object Compositing from Image Intrinsics via Diffusion
Zitian Zhang, Frédéric Fortier-Chouinard, Mathieu Garon +2
We present ZeroComp, an effective zero-shot 3D object compositing approach that does not require paired composite-scene images during training. Our method leverages ControlNet to c…
A Diffusion Approach to Radiance Field Relighting using Multi-Illumination Synthesis
Yohan Poirier-Ginter, Alban Gauthier, Julien Philip +2
Relighting radiance fields is severely underconstrained for multi-view data, which is most often captured under a single illumination condition; It is especially hard for full scen…
PanDORA: Casual HDR Radiance Acquisition of Indoor Scenes for Image-based Lighting
Mohammad Reza Karimi Dastjerdi, Dominique Tanguay-Gaudreau, Frédéric Fortier-Chouinard +3
Most novel view synthesis methods -- including Neural Radiance Fields (NeRF) -- struggle to capture the high dynamic range (HDR) radiance required for realistic image-based lightin…
Towards a Perceptual Evaluation Framework for Lighting Estimation
Justine Giroux, Mohammad Reza Karimi Dastjerdi, Yannick Hold-Geoffroy +2
Progress in lighting estimation is tracked by computing existing image quality assessment (IQA) metrics on images from standard datasets. While this may appear to be a reasonable a…