Results 21 to 30 of about 7,112 (233)

3D representation of Architectural Heritage: a comparative analysis of NeRF, Gaussian Splatting, and SfM-MVS reconstructions using low-cost sensors [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
This study evaluates the performance of three image-based 3D reconstruction methods—Structure-from-Motion with Multi-View Stereo (SfM-MVS), Neural Radiance Fields (NeRF), and Gaussian Splatting (GS)—for documenting Architectural Heritage (AH).
P. Clini, R. Nespeca, R. Angeloni, L. Coppetta   +3 more
doaj   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

MEIL-NeRF: Memory-Efficient Incremental Learning of Neural Radiance Fields

IEEE Access
Hinged on the representation power of neural networks, neural radiance fields (NeRF) have recently emerged as one of the promising and widely applicable methods for 3D object and scene representation.
Jaeyoung Chung, Kanggeon Lee, Sungyong Baik, Kyoung Mu Lee   +3 more
doaj   +1 more source

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

Neural Radiance Field-Inspired Depth Map Refinement for Accurate Multi-View Stereo

Journal of Imaging
In this paper, we propose a method to refine the depth maps obtained by Multi-View Stereo (MVS) through iterative optimization of the Neural Radiance Field (NeRF).
Shintaro Ito, Kanta Miura, Koichi Ito, Takafumi Aoki   +3 more
doaj   +1 more source

Promoting Fun or Competition? Testing Interventions on Ludic and Agonistic Work Design

Journal of Organizational Behavior, EarlyView.
ABSTRACT Research highlights the benefits of play‐at‐work, yet little is known about training employees to self‐initiate it. We tested two programs to train employees on designing work with elements of fun (ludic work design [LWD]) or competition (agonistic work design [AWD]).
Jan E. Walsken, Fabiola H. Gerpott, Carl Marcus Wallenburg   +2 more
wiley   +1 more source

Comparative verification of 3D reconstructed point cloud data: comparison of AI estimation and multi-view stereo methods using Nerfstudio and Metashape

SICE Journal of Control, Measurement, and System Integration
We investigated the feasibility of using a 3D point cloud estimated by a neural radiance field (NeRF). We evaluated the quality of point clouds reconstructed with NeRF and multi-view stereo.
Yuta Tsukamoto, Atsushi Hayashi, Kenichi Tokuda, Nobuo Kochi   +3 more
doaj   +1 more source

PIE-NeRF: Physics-Based Interactive Elastodynamics with NeRF

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
We show that physics-based simulations can be seamlessly integrated with NeRF to generate high-quality elastodynamics of real-world objects. Unlike existing methods, we discretize nonlinear hyperelasticity in a meshless way, obviating the necessity for intermediate auxiliary shape proxies like a tetrahedral mesh or voxel grid.
Feng, Yutao, Shang, Yintong, Li, Xuan, Shao, Tianjia, Jiang, Chenfanfu, Yang, Yin   +5 more
openaire   +2 more sources

Splatshop: Efficiently Editing Large Gaussian Splat Models

Computer Graphics Forum, EarlyView.
Abstract We present Splatshop, a highly optimized toolbox for interactive editing (selection, deletion, painting, transformation, …) of 3D Gaussian Splatting models. Utilizing a comprehensive collection of heuristic approaches, we carefully balance between exact and fast rendering to enable precise editing without sacrificing real‐time performance. Our
Markus Schütz, Christoph Peters, Florian Hahlbohm, Elmar Eisemann, Marcus Magnor, Michael Wimmer   +5 more
wiley   +1 more source

PSHead: 3D Head Reconstruction from a Single Image with Diffusion Prior and Self‐Enhancement

Computer Graphics Forum, EarlyView.
We introduce PSHead, a coarse‐to‐fine framework guided by both object and face priors, to produce a Gaussian‐based 3D avatar for a single frontal‐view reference image. In the coarse stage, we create an initial 3D representation by applying diffusion models trained for general object generation, using Score Distillation Sampling losses over novel views.
Jing Yang, Tianhan Wu, Kyle Fogarty, Fangcheng Zhong, Cengiz Oztireli   +4 more
wiley   +1 more source