Neural radiance fields in the industrial and robotics domain: applications, research opportunities and use cases

E Šlapak, E Pardo, M Dopiriak, T Maksymyuk… - Robotics and Computer …, 2024 - Elsevier
The proliferation of technologies, such as extended reality (XR), has increased the demand
for high-quality three-dimensional (3D) graphical representations. Industrial 3D applications …

Pie-nerf: Physics-based interactive elastodynamics with nerf

Y Feng, Y Shang, X Li, T Shao… - Proceedings of the …, 2024 - openaccess.thecvf.com
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 …

Interactive nerf geometry editing with shape priors

YJ Yuan, YT Sun, YK Lai, Y Ma, R Jia… - … on Pattern Analysis …, 2023 - ieeexplore.ieee.org
Neural Radiance Fields (NeRFs) have shown great potential for tasks like novel view
synthesis of static 3D scenes. Since NeRFs are trained on a large number of input images, it …

Deformable model-driven neural rendering for high-fidelity 3D reconstruction of human heads under low-view settings

B Xu, J Zhang, KY Lin, C Qian… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Reconstructing 3D human heads in low-view settings presents technical challenges, mainly
due to the pronounced risk of overfitting with limited views and high-frequency signals. To …

NeRF in Robotics: A Survey

G Wang, L Pan, S Peng, S Liu, C Xu, Y Miao… - arXiv preprint arXiv …, 2024 - arxiv.org
Meticulous 3D environment representations have been a longstanding goal in computer
vision and robotics fields. The recent emergence of neural implicit representations has …

Efficient ray sampling for radiance fields reconstruction

S Sun, M Liu, Z Fan, Q Jiao, Y Liu, L Dong, L Kong - Computers & Graphics, 2024 - Elsevier
Accelerating the training process of neural radiance field holds substantial practical value.
The ray sampling strategy profoundly influences the convergence of this neural network …

Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs

M Kim, K Jun-Seong, SY Yun, JH Kim - Forty-first International …, 2024 - openreview.net
The multi-plane representation has been highlighted for its fast training and inference across
static and dynamic neural radiance fields. This approach constructs relevant features via …

Scene-Constrained Neural Radiance Fields for High-Quality Sports Scene Rendering Based on Visual Sensor Network

Y Dai, J Li, Y Zhang, Y Jiang, H Qin, X Zhou… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Free-viewpoint videos offer audiences a more immersive and liberated way to watch sports.
The rendering of sports scenes encompasses two essential elements: dynamic targets and …

Intensity Field Decomposition for Tissue-Guided Neural Tomography

MX Li, JG Yu, Y Gao, C Huang, GS Xia - arXiv preprint arXiv:2411.00900, 2024 - arxiv.org
Cone-beam computed tomography (CBCT) typically requires hundreds of X-ray projections,
which raises concerns about radiation exposure. While sparse-view reconstruction reduces …

Few-Shot Neural Radiance Fields under Unconstrained Illumination

SY Lee, JY Choi, S Kim, IJ Kim, J Cho - Proceedings of the AAAI …, 2024 - ojs.aaai.org
In this paper, we introduce a new challenge for synthesizing novel view images in practical
environments with limited input multi-view images and varying lighting conditions. Neural …