20 citations · 72 across the 25 of their papers we have counts for
8 papers · 1 filter
Generative Multiview Relighting for 3D Reconstruction under Extreme Illumination Variation
Hadi Alzayer, Philipp Henzler, Jonathan T. Barron +3
Reconstructing the geometry and appearance of objects from photographs taken in different environments is difficult as the illumination and therefore the object appearance vary acr…
SimVS: Simulating World Inconsistencies for Robust View Synthesis
Alex Trevithick, Roni Paiss, Philipp Henzler +9
Novel-view synthesis techniques achieve impressive results for static scenes but struggle when faced with the inconsistencies inherent to casual capture settings: varying illuminat…
EVER: Exact Volumetric Ellipsoid Rendering for Real-time View Synthesis
Alexander Mai, Peter Hedman, George Kopanas +6
We present Exact Volumetric Ellipsoid Rendering (EVER), a method for real-time differentiable emission-only volume rendering. Unlike recent rasterization based approach by 3D Gauss…
Flash Cache: Reducing Bias in Radiance Cache Based Inverse Rendering
Benjamin Attal, Dor Verbin, Ben Mildenhall +4
State-of-the-art techniques for 3D reconstruction are largely based on volumetric scene representations, which require sampling multiple points to compute the color arriving along…
IllumiNeRF: 3D Relighting Without Inverse Rendering
Xiaoming Zhao, Pratul P. Srinivasan, Dor Verbin +3
Existing methods for relightable view synthesis -- using a set of images of an object under unknown lighting to recover a 3D representation that can be rendered from novel viewpoin…
NeRF-Casting: Improved View-Dependent Appearance with Consistent Reflections
Dor Verbin, Pratul P. Srinivasan, Peter Hedman +4
Neural Radiance Fields (NeRFs) typically struggle to reconstruct and render highly specular objects, whose appearance varies quickly with changes in viewpoint. Recent works have im…
Binary Opacity Grids: Capturing Fine Geometric Detail for Mesh-Based View Synthesis
Christian Reiser, Stephan Garbin, Pratul P. Srinivasan +6
While surface-based view synthesis algorithms are appealing due to their low computational requirements, they often struggle to reproduce thin structures. In contrast, more expensi…
Boundary Attention: Learning curves, corners, junctions and grouping
Mia Gaia Polansky, Charles Herrmann, Junhwa Hur +3
We present a lightweight network that infers grouping and boundaries, including curves, corners and junctions. It operates in a bottom-up fashion, analogous to classical methods fo…