Results 1 to 10 of about 14,278 (275)

Remote Sensing Neural Radiance Fields for Multi-View Satellite Photogrammetry

Remote Sensing, 2023
Neural radiance fields (NeRFs) combining machine learning with differentiable rendering have arisen as one of the most promising approaches for novel view synthesis and depth estimates.
Songlin Xie, Lei Zhang, Gwanggil Jeon, Xiaomin Yang   +3 more
doaj   +3 more sources

Neural Radiance Fields for High-Fidelity Soft Tissue Reconstruction in Endoscopy [PDF]

Sensors
The advancement of neural radiance fields (NeRFs) has facilitated the high-quality 3D reconstruction of complex scenes. However, for most NeRFs, reconstructing 3D tissues from endoscopy images poses significant challenges due to the occlusion of soft ...
Jinhua Liu, Yongsheng Shi, Dongjin Huang, Jiantao Qu   +3 more
doaj   +2 more sources

Neural radiance fields assisted by image features for UAV scene reconstruction [PDF]

Scientific Reports
With the rapid advancement of Unmanned Aerial Vehicle applications, vision-based 3D scene reconstruction has demonstrated significant value in fields such as remote sensing and target detection.
Zhihong Chen, Xueyun Chen, Chenghong Ye, Shaojie Wu, Xiang Wu   +4 more
doaj   +2 more sources

Multi-channel volume density neural radiance field for hyperspectral imaging [PDF]

Scientific Reports
Hyperspectral imaging and Neural Radiance Field (NeRF) can be combined in powerful ways. With limited hyperspectral images, NeRF can generate images of objects with spectral information from arbitrary viewpoints, which can effectively mitigate defects ...
Runchuan Ma, Sailing He
doaj   +2 more sources

SonoNERFs: Neural Radiance Fields Applied to Biological Echolocation Systems Allow 3D Scene Reconstruction through Perceptual Prediction [PDF]

Biomimetics
In this paper, we introduce SonoNERFs, a novel approach that adapts Neural Radiance Fields (NeRFs) to model and understand the echolocation process in bats, focusing on the challenges posed by acoustic data interpretation without phase information ...
Wouter Jansen, Jan Steckel
doaj   +2 more sources

MBS-NeRF: reconstruction of sharp neural radiance fields from motion-blurred sparse images [PDF]

Scientific Reports
The recent advance in Neural Radiance Fields (NeRF), which utilizes Multilayer Perceptrons (MLP) for implicit scene representation, enables the synthesis of realistic views from new perspectives.
Changbo Gao, Qiucheng Sun, Jinlong Zhu, Jie Chen   +3 more
doaj   +2 more sources

Evaluating Neural Radiance Fields for 3D Plant Geometry Reconstruction in Field Conditions [PDF]

Plant Phenomics
We evaluate different Neural Radiance Field (NeRF) techniques for the 3D reconstruction of plants in varied environments, from indoor settings to outdoor fields.
Muhammad Arbab Arshad, Talukder Jubery, James Afful, Anushrut Jignasu, Aditya Balu, Baskar Ganapathysubramanian, Soumik Sarkar, Adarsh Krishnamurthy   +7 more
doaj   +2 more sources

NeRFlex: Flexible Neural Radiance Fields With Diffeomorphic Deformation

IEEE Access
Due to the vast array of NeRF-based techniques, the representation power of Neural Radiance Fields (NeRF) has been quickly rising in recent years. However, it is still difficult to offer fresh perspectives for user-controlled geometry alterations with ...
Jiyoon Shin, Sangwoo Hong, Jungwoo Lee
doaj   +3 more sources

Bio-Inspired 3D Affordance Understanding from Single Image with Neural Radiance Field for Enhanced Embodied Intelligence [PDF]

Biomimetics
Affordance understanding means identifying possible operable parts of objects, which is crucial in achieving accurate robotic manipulation. Although homogeneous objects for grasping have various shapes, they always share a similar affordance distribution.
Zirui Guo, Xieyuanli Chen, Zhiqiang Zheng, Huimin Lu, Ruibin Guo   +4 more
doaj   +2 more sources

DOUBLE NERF: REPRESENTING DYNAMIC SCENES AS NEURAL RADIANCE FIELDS [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023
Neural Radiance Fields (NeRFs) are non-convolutional neural models that learn 3D scene structure and color to produce novel images of a given scene from a new view point.
V. V. Kniaz, V. V. Kniaz, V. A. Knyaz, V. A. Knyaz, A. Bordodymov, P. Moshkantsev, D. Novikov, S. Barylnik   +7 more
doaj   +1 more source