Relightable 3d gaussians: Realistic point cloud relighting with brdf decomposition and ray tracing
In this paper, we present a novel differentiable point-based rendering framework to achieve
photo-realistic relighting. To make the reconstructed scene relightable, we enhance vanilla …
photo-realistic relighting. To make the reconstructed scene relightable, we enhance vanilla …
Benchmarking neural radiance fields for autonomous robots: An overview
Abstract Neural Radiance Field (NeRF) has emerged as a powerful paradigm for scene
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …
Dreammat: High-quality pbr material generation with geometry-and light-aware diffusion models
Recent advancements in 2D diffusion models allow appearance generation on untextured
raw meshes. These methods create RGB textures by distilling a 2D diffusion model, which …
raw meshes. These methods create RGB textures by distilling a 2D diffusion model, which …
Intrinsicanything: Learning diffusion priors for inverse rendering under unknown illumination
This paper aims to recover object materials from posed images captured under an unknown
static lighting condition. Recent methods solve this task by optimizing material parameters …
static lighting condition. Recent methods solve this task by optimizing material parameters …
Flash cache: Reducing bias in radiance cache based inverse rendering
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 …
representations, which require sampling multiple points to compute the color arriving along …
Specnerf: Gaussian directional encoding for specular reflections
Neural radiance fields have achieved remarkable performance in modeling the appearance
of 3D scenes. However existing approaches still struggle with the view-dependent …
of 3D scenes. However existing approaches still struggle with the view-dependent …
A Diffusion Approach to Radiance Field Relighting using Multi‐Illumination Synthesis
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 scenes …
often captured under a single illumination condition; It is especially hard for full scenes …
Gir: 3d gaussian inverse rendering for relightable scene factorization
This paper presents GIR, a 3D Gaussian Inverse Rendering method for relightable scene
factorization. Compared to existing methods leveraging discrete meshes or neural implicit …
factorization. Compared to existing methods leveraging discrete meshes or neural implicit …
NeISF: Neural Incident Stokes Field for Geometry and Material Estimation
Multi-view inverse rendering is the problem of estimating the scene parameters such as
shapes materials or illuminations from a sequence of images captured under different …
shapes materials or illuminations from a sequence of images captured under different …
NeuralTO: Neural Reconstruction and View Synthesis of Translucent Objects
Learning from multi-view images using neural implicit signed distance functions shows
impressive performance on 3D Reconstruction of opaque objects. However, existing …
impressive performance on 3D Reconstruction of opaque objects. However, existing …