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 …
Flipnerf: Flipped reflection rays for few-shot novel view synthesis
Abstract Neural Radiance Field (NeRF) has been a mainstream in novel view synthesis with
its remarkable quality of rendered images and simple architecture. Although NeRF has been …
its remarkable quality of rendered images and simple architecture. Although NeRF has been …
Simplenerf: Regularizing sparse input neural radiance fields with simpler solutions
N Somraj, A Karanayil, R Soundararajan - SIGGRAPH Asia 2023 …, 2023 - dl.acm.org
Neural Radiance Fields (NeRF) show impressive performance for the photo-realistic free-
view rendering of scenes. However, NeRFs require dense sampling of images in the given …
view rendering of scenes. However, NeRFs require dense sampling of images in the given …
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 …
Is vanilla MLP in neural radiance field enough for few-shot view synthesis?
Abstract Neural Radiance Field (NeRF) has achieved superior performance for novel view
synthesis by modeling the scene with a Multi-Layer Perception (MLP) and a volume …
synthesis by modeling the scene with a Multi-Layer Perception (MLP) and a volume …
Deceptive-nerf: Enhancing nerf reconstruction using pseudo-observations from diffusion models
We introduce Deceptive-NeRF, a novel methodology for few-shot NeRF reconstruction,
which leverages diffusion models to synthesize plausible pseudo-observations to improve …
which leverages diffusion models to synthesize plausible pseudo-observations to improve …
Neural Radiance Field-based Visual Rendering: A Comprehensive Review
In recent years, Neural Radiance Fields (NeRF) has made remarkable progress in the field
of computer vision and graphics, providing strong technical support for solving key tasks …
of computer vision and graphics, providing strong technical support for solving key tasks …
Fast sun-aligned outdoor scene relighting based on tensorf
In this work, we introduce our method of outdoor scene relighting for Neural Radiance Fields
(NeRF) named Sun-aligned Relighting TensoRF (SR-TensoRF). SR-TensoRF offers a …
(NeRF) named Sun-aligned Relighting TensoRF (SR-TensoRF). SR-TensoRF offers a …
PoseDiff: Pose-conditioned Multimodal Diffusion Model for Unbounded Scene Synthesis from Sparse Inputs
Novel view synthesis has been heavily driven by NeRF-based models, but these models
often hold limitations with the requirement of dense coverage of input views and expensive …
often hold limitations with the requirement of dense coverage of input views and expensive …
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 …