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View article: Generative Multiview Relighting for 3D Reconstruction under Extreme Illumination Variation
Generative Multiview Relighting for 3D Reconstruction under Extreme Illumination Variation Open
Reconstructing the geometry and appearance of objects from photographs taken in different environments is difficult as the illumination and therefore the object appearance vary across captured images. This is particularly challenging for m…
View article: SimVS: Simulating World Inconsistencies for Robust View Synthesis
SimVS: Simulating World Inconsistencies for Robust View Synthesis Open
Novel-view synthesis techniques achieve impressive results for static scenes but struggle when faced with the inconsistencies inherent to casual capture settings: varying illumination, scene motion, and other unintended effects that are di…
View article: EVER: Exact Volumetric Ellipsoid Rendering for Real-time View Synthesis
EVER: Exact Volumetric Ellipsoid Rendering for Real-time View Synthesis Open
We present Exact Volumetric Ellipsoid Rendering (EVER), a method for real-time differentiable emission-only volume rendering. Unlike recent rasterization based approach by 3D Gaussian Splatting (3DGS), our primitive based representation al…
View article: Flash Cache: Reducing Bias in Radiance Cache Based Inverse Rendering
Flash Cache: Reducing Bias in Radiance Cache Based Inverse Rendering Open
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 a ray. Using these representations for more general inverse…
View article: IllumiNeRF: 3D Relighting Without Inverse Rendering
IllumiNeRF: 3D Relighting Without Inverse Rendering Open
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 viewpoints under a target illumination -- are based on inverse rend…
View article: NeRF-Casting: Improved View-Dependent Appearance with Consistent Reflections
NeRF-Casting: Improved View-Dependent Appearance with Consistent Reflections Open
Neural Radiance Fields (NeRFs) typically struggle to reconstruct and render highly specular objects, whose appearance varies quickly with changes in viewpoint. Recent works have improved NeRF's ability to render detailed specular appearanc…
View article: Binary Opacity Grids: Capturing Fine Geometric Detail for Mesh-Based View Synthesis
Binary Opacity Grids: Capturing Fine Geometric Detail for Mesh-Based View Synthesis Open
While surface-based view synthesis algorithms are appealing due to their low computational requirements, they often struggle to reproduce thin structures. In contrast, more expensive methods that model the scene's geometry as a volumetric …
View article: Boundary Attention: Learning curves, corners, junctions and grouping
Boundary Attention: Learning curves, corners, junctions and grouping Open
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 for sub-pixel edge localization and edge-linking, but with a …
View article: Nuvo: Neural UV Mapping for Unruly 3D Representations
Nuvo: Neural UV Mapping for Unruly 3D Representations Open
Existing UV mapping algorithms are designed to operate on well-behaved meshes, instead of the geometry representations produced by state-of-the-art 3D reconstruction and generation techniques. As such, applying these methods to the volume …
View article: ReconFusion: 3D Reconstruction with Diffusion Priors
ReconFusion: 3D Reconstruction with Diffusion Priors Open
3D reconstruction methods such as Neural Radiance Fields (NeRFs) excel at rendering photorealistic novel views of complex scenes. However, recovering a high-quality NeRF typically requires tens to hundreds of input images, resulting in a t…
View article: Generative Powers of Ten
Generative Powers of Ten Open
We present a method that uses a text-to-image model to generate consistent content across multiple image scales, enabling extreme semantic zooms into a scene, e.g., ranging from a wide-angle landscape view of a forest to a macro shot of an…
View article: BakedSDF: Meshing Neural SDFs for Real-Time View Synthesis
BakedSDF: Meshing Neural SDFs for Real-Time View Synthesis Open
We present a method for reconstructing high-quality meshes of large unbounded real-world scenes suitable for photorealistic novel view synthesis. We first optimize a hybrid neural volume-surface scene representation designed to have well-b…
View article: Eclipse: Disambiguating Illumination and Materials using Unintended Shadows
Eclipse: Disambiguating Illumination and Materials using Unintended Shadows Open
Decomposing an object's appearance into representations of its materials and the surrounding illumination is difficult, even when the object's 3D shape is known beforehand. This problem is especially challenging for diffuse objects: it is …
View article: Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields
Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields Open
Neural Radiance Field training can be accelerated through the use of grid-based representations in NeRF's learned mapping from spatial coordinates to colors and volumetric density. However, these grid-based approaches lack an explicit unde…
View article: Neural Microfacet Fields for Inverse Rendering
Neural Microfacet Fields for Inverse Rendering Open
We present Neural Microfacet Fields, a method for recovering materials, geometry, and environment illumination from images of a scene. Our method uses a microfacet reflectance model within a volumetric setting by treating each sample along…
View article: BakedSDF: Meshing Neural SDFs for Real-Time View Synthesis
BakedSDF: Meshing Neural SDFs for Real-Time View Synthesis Open
We present a method for reconstructing high-quality meshes of large unbounded real-world scenes suitable for photorealistic novel view synthesis. We first optimize a hybrid neural volume-surface scene representation designed to have well-b…
View article: MERF: Memory-Efficient Radiance Fields for Real-time View Synthesis in Unbounded Scenes
MERF: Memory-Efficient Radiance Fields for Real-time View Synthesis in Unbounded Scenes Open
Neural radiance fields enable state-of-the-art photorealistic view synthesis. However, existing radiance field representations are either too compute-intensive for real-time rendering or require too much memory to scale to large scenes. We…
View article: Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields
Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields Open
Neural Radiance Fields (NeRF) is a popular view synthesis technique that represents a scene as a continuous volumetric function, parameterized by multilayer perceptrons that provide the volume density and view-dependent emitted radiance at…
View article: Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields
Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields Open
Though neural radiance fields (NeRF) have demonstrated impressive view synthesis results on objects and small bounded regions of space, they struggle on "unbounded" scenes, where the camera may point in any direction and content may exist …
View article: Unique Geometry and Texture From Corresponding Image Patches
Unique Geometry and Texture From Corresponding Image Patches Open
We present a sufficient condition for recovering unique texture and viewpoints from unknown orthographic projections of a flat texture process. We show that four observations are sufficient in general, and we characterize the ambiguous cas…
View article: Field of Junctions: Extracting Boundary Structure at Low SNR
Field of Junctions: Extracting Boundary Structure at Low SNR Open
We introduce a bottom-up model for simultaneously finding many boundary elements in an image, including contours, corners and junctions. The model explains boundary shape in each small patch using a 'generalized M-junction' comprising M an…
View article: Field of Junctions.
Field of Junctions. Open
We introduce a bottom-up model for jointly finding many boundary elements in an image, including edges, curves, corners and junctions. The model explains boundary shape in each small patch using a junction with M angles and a freely-moving…