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 …
Wordepth: Variational language prior for monocular depth estimation
Abstract Three-dimensional (3D) reconstruction from a single image is an ill-posed problem
with inherent ambiguities ie scale. Predicting a 3D scene from text description (s) is similarly …
with inherent ambiguities ie scale. Predicting a 3D scene from text description (s) is similarly …
Epic fields: Marrying 3d geometry and video understanding
V Tschernezki, A Darkhalil, Z Zhu… - Advances in …, 2024 - proceedings.neurips.cc
Neural rendering is fuelling a unification of learning, 3D geometry and video understanding
that has been waiting for more than two decades. Progress, however, is still hampered by a …
that has been waiting for more than two decades. Progress, however, is still hampered by a …
Gaufre: Gaussian deformation fields for real-time dynamic novel view synthesis
We propose a method for dynamic scene reconstruction using deformable 3D Gaussians
that is tailored for monocular video. Building upon the efficiency of Gaussian splatting, our …
that is tailored for monocular video. Building upon the efficiency of Gaussian splatting, our …
When Does Perceptual Alignment Benefit Vision Representations?
Humans judge perceptual similarity according to diverse visual attributes, including scene
layout, subject location, and camera pose. Existing vision models understand a wide range …
layout, subject location, and camera pose. Existing vision models understand a wide range …
Flowed Time of Flight Radiance Fields
Flowed time of flight radiance fields (F-TöRF) is a method to correct for motion artifacts in
continuous-wave time of flight imaging (C-ToF). As C-ToF cameras must capture multiple …
continuous-wave time of flight imaging (C-ToF). As C-ToF cameras must capture multiple …
DGD: Dynamic 3D Gaussians Distillation
We tackle the task of learning dynamic 3D semantic radiance fields given a single
monocular video as input. Our learned semantic radiance field captures per-point semantics …
monocular video as input. Our learned semantic radiance field captures per-point semantics …
Grid4D: 4D Decomposed Hash Encoding for High-fidelity Dynamic Gaussian Splatting
J Xu, Z Fan, J Yang, J Xie - arXiv preprint arXiv:2410.20815, 2024 - arxiv.org
Recently, Gaussian splatting has received more and more attention in the field of static
scene rendering. Due to the low computational overhead and inherent flexibility of explicit …
scene rendering. Due to the low computational overhead and inherent flexibility of explicit …
[图书][B] Computer Vision-ECCV 2024: 18th European Conference, Milan, Italy, September 29-October 4, 2024, Proceedings, Part XXIV.
A Leonardis - 2024 - books.google.com
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes
the refereed proceedings of the 18th European Conference on Computer Vision, ECCV …
the refereed proceedings of the 18th European Conference on Computer Vision, ECCV …
[PDF][PDF] DGD: Dynamic 3D Gaussians Distillation
ILNII Lang, S Benaim - fq.pkwyx.com
We tackle the task of learning dynamic 3D semantic radiance fields given a single
monocular video as input. Our learned semantic radiance field captures per-point semantics …
monocular video as input. Our learned semantic radiance field captures per-point semantics …