Reconfusion: 3d reconstruction with diffusion priors
Abstract 3D reconstruction methods such as Neural Radiance Fields (NeRFs) excel at
rendering photorealistic novel views of complex scenes. However recovering a high-quality …
rendering photorealistic novel views of complex scenes. However recovering a high-quality …
Dngaussian: Optimizing sparse-view 3d gaussian radiance fields with global-local depth normalization
Radiance fields have demonstrated impressive performance in synthesizing novel views
from sparse input views yet prevailing methods suffer from high training costs and slow …
from sparse input views yet prevailing methods suffer from high training costs and slow …
Semantically-aware Neural Radiance Fields for Visual Scene Understanding: A Comprehensive Review
TAQ Nguyen, A Bourki, M Macudzinski… - arXiv preprint arXiv …, 2024 - arxiv.org
This review thoroughly examines the role of semantically-aware Neural Radiance Fields
(NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. It …
(NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. It …
Reducing shape-radiance ambiguity in radiance fields with a closed-form color estimation method
Neural radiance field (NeRF) enables the synthesis of cutting-edge realistic novel view
images of a 3D scene. It includes density and color fields to model the shape and radiance …
images of a 3D scene. It includes density and color fields to model the shape and radiance …
Nerf revisited: Fixing quadrature instability in volume rendering
Neural radiance fields (NeRF) rely on volume rendering to synthesize novel views. Volume
rendering requires evaluating an integral along each ray, which is numerically approximated …
rendering requires evaluating an integral along each ray, which is numerically approximated …
Därf: Boosting radiance fields from sparse input views with monocular depth adaptation
Neural radiance field (NeRF) shows powerful performance in novel view synthesis and 3D
geometry reconstruction, but it suffers from critical performance degradation when the …
geometry reconstruction, but it suffers from critical performance degradation when the …
Global and Hierarchical Geometry Consistency Priors for Few-shot NeRFs in Indoor Scenes
X Sun, Q Xu, X Yang, Y Zang… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
It is challenging for Neural Radiance Fields (NeRFs) in the few-shot setting to reconstruct
high-quality novel views and depth maps in 360^\circ outward-facing indoor scenes. The …
high-quality novel views and depth maps in 360^\circ outward-facing indoor scenes. The …
G3DR: Generative 3D Reconstruction in ImageNet
We introduce a novel 3D generative method Generative 3D Reconstruction (G3DR) in
ImageNet capable of generating diverse and high-quality 3D objects from single images …
ImageNet capable of generating diverse and high-quality 3D objects from single images …
High-Resolution and Few-Shot View Synthesis from Asymmetric Dual-Lens Inputs
Novel view synthesis has achieved remarkable quality and efficiency by the paradigm of 3D
Gaussian Splatting (3D-GS), but still faces two challenges: 1) significant performance …
Gaussian Splatting (3D-GS), but still faces two challenges: 1) significant performance …
BoostMVSNeRFs: Boosting MVS-based NeRFs to Generalizable View Synthesis in Large-scale Scenes
While Neural Radiance Fields (NeRFs) have demonstrated exceptional quality, their
protracted training duration remains a limitation. Generalizable and MVS-based NeRFs …
protracted training duration remains a limitation. Generalizable and MVS-based NeRFs …