Results 1 to 10 of about 8,359,557 (286)

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   +3 more sources

SpiNeRF: direct-trained spiking neural networks for efficient neural radiance field rendering [PDF]

Frontiers in Neuroscience
Spiking neural networks (SNNs) have recently demonstrated significant progress across various computational tasks, due to their potential for energy efficiency.
Xingting Yao, Xingting Yao, Qinghao Hu, Fei Zhou, Tielong Liu, Tielong Liu, Zitao Mo, Zeyu Zhu, Zeyu Zhu, Zhengyang Zhuge, Jian Cheng, Jian Cheng   +11 more
doaj   +4 more sources

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

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   +4 more sources

Evaluating the Effectiveness of Neural Radiance Field for Noninvasive Volumetric Assessment [PDF]

Plastic and Reconstructive Surgery, Global Open
Summary:. Assessing swelling is crucial for the surgical treatment of lower limb lymphedema and is often conducted using 2-dimensional (2D) imaging, which is available in most outpatient settings. Advanced methods, such as taping and computed tomography (
Soma Nakaso, MD, Hyakuzoh Ueda, MD, Shimpei Ono, MD, PhD, Rei Ogawa, MD, PhD   +3 more
doaj   +2 more sources

Neural Radiance Field Dynamic Scene SLAM Based on Ray Segmentation and Bundle Adjustment [PDF]

Sensors
The current neural implicit SLAM methods have demonstrated excellent performance in reconstructing ideal static 3D scenes. However, it remains a significant challenge for these methods to handle real scenes with drastic changes in lighting conditions and
Yuquan Zhang, Guosheng Feng
doaj   +2 more sources

Inspection-Nerf: Rendering Multi-Type Local Images for Dam Surface Inspection Task Using Climbing Robot and Neural Radiance Field

Buildings, 2023
For the surface defects inspection task, operators need to check the defect in local detail images by specifying the location, which only the global 3D model reconstruction can’t satisfy.
Kunlong Hong, Hongguang Wang, Bingbing Yuan   +2 more
doaj   +3 more sources

Unmanned Aerial Vehicle-Neural Radiance Field (UAV-NeRF): Learning Multiview Drone Three-Dimensional Reconstruction with Neural Radiance Field

Remote Sensing
In traditional 3D reconstruction using UAV images, only radiance information, which is treated as a geometric constraint, is used in feature matching, allowing for the restoration of the scene’s structure. After introducing radiance supervision, NeRF can
Li Li, Yongsheng Zhang, Zhipeng Jiang, Ziquan Wang, Lei Zhang, Han Gao   +5 more
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

Recovering Scene Geometry and Material from Event Streams with 3D Gaussian Splatting [PDF]

Sensors
Recovering scene geometry and material yields physically meaningful representations that support many tasks in computer vision and graphics. Methods built on neural representations such as neural radiance fields and 3D Gaussian Splatting perform well but
Zehao Chen, Binbin Zhou, Zengwei Zheng
doaj   +2 more sources

A benchmark dataset for objective quality assessment of view synthesis for neural radiance field (NeRF)Figshare [PDF]

Data in Brief
Neural Radiance Fields (NeRF) are revolutionizing diverse fields such as autonomous driving, education, and virtual reality (VR). As their applications expand, the ability to accurately evaluate the quality of NeRF-generated content becomes essential ...
Chibuike Onuoha, Shihao Luo, Jean Flaherty, Truong Thu Huong, Pham Ngoc Nam, Truong Cong Thang   +5 more
doaj   +2 more sources