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 …
Scene reconstruction techniques for autonomous driving: a review of 3D Gaussian splatting
H Zhu, Z Zhang, J Zhao, H Duan, Y Ding, X Xiao… - Artificial Intelligence …, 2025 - Springer
As the latest research result of the explicit radiated field technology, 3D Gaussian Splatting
(3D GS) replaces the implicit expression represented by Neural Radiated Field (NeRF) and …
(3D GS) replaces the implicit expression represented by Neural Radiated Field (NeRF) and …
Multi-task View Synthesis with Neural Radiance Fields
Multi-task visual learning is a critical aspect of computer vision. Current research, however,
predominantly concentrates on the multi-task dense prediction setting, which overlooks the …
predominantly concentrates on the multi-task dense prediction setting, which overlooks the …
Omni-Recon: Harnessing Image-Based Rendering for General-Purpose Neural Radiance Fields
Abstract Recent breakthroughs in Neural Radiance Fields (NeRFs) have sparked significant
demand for their integration into real-world 3D applications. However, the varied …
demand for their integration into real-world 3D applications. However, the varied …
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models
Beyond high-fidelity image synthesis, diffusion models have recently exhibited promising
results in dense visual perception tasks. However, most existing work treats diffusion models …
results in dense visual perception tasks. However, most existing work treats diffusion models …
Omni-Recon: Towards General-Purpose Neural Radiance Fields for Versatile 3D Applications
Recent breakthroughs in Neural Radiance Fields (NeRFs) have sparked significant demand
for their integration into real-world 3D applications. However, the varied functionalities …
for their integration into real-world 3D applications. However, the varied functionalities …
MomentsNeRF: Leveraging Orthogonal Moments for Few-Shot Neural Rendering
We propose MomentsNeRF, a novel framework for one-and few-shot neural rendering that
predicts a neural representation of a 3D scene using Orthogonal Moments. Our architecture …
predicts a neural representation of a 3D scene using Orthogonal Moments. Our architecture …
Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methods
A Mumuni, F Mumuni - arXiv preprint arXiv:2403.08352, 2024 - arxiv.org
Data augmentation is arguably the most important regularization technique commonly used
to improve generalization performance of machine learning models. It primarily involves the …
to improve generalization performance of machine learning models. It primarily involves the …
IS-NEAR: Implicit Semantic Neural Engine and Multi-Sensor Data Rendering With 3D Global Feature
Data-driven Computer Vision (CV) tasks are still limited by the amount of labeled data.
Recently, some semantic NeRFs have been proposed to render and synthesize novel-view …
Recently, some semantic NeRFs have been proposed to render and synthesize novel-view …
Enhancing Neural Radiance Fields with Depth and Normal Completion Priors from Sparse Views
J Guo, HC Chou, N Ding - arXiv preprint arXiv:2407.05666, 2024 - arxiv.org
Neural Radiance Fields (NeRF) are an advanced technology that creates highly realistic
images by learning about scenes through a neural network model. However, NeRF often …
images by learning about scenes through a neural network model. However, NeRF often …