Results 121 to 130 of about 4,408 (223)

Neural Field-Based Space Target 3D Reconstruction with Predicted Depth Priors

Aerospace
As space technology advances, an increasing number of spacecrafts are being launched into space, making it essential to monitor and maintain satellites to ensure safe and stable operations.
Tao Fu, Yu Zhou, Ying Wang, Jian Liu, Yamin Zhang, Qinglei Kong, Bo Chen   +6 more
doaj   +1 more source

ActiveNeRF: Learning where to See with Uncertainty Estimation

, 2022
Recently, Neural Radiance Fields (NeRF) has shown promising performances on reconstructing 3D scenes and synthesizing novel views from a sparse set of 2D images.
Huang, Gao, Lai, Zihang, Pan, Xuran, Song, Shiji   +3 more
core  

F2Plenoxels: fast voxel radiance fields without neural networks for few-shot view synthesis

Journal of King Saud University: Computer and Information Sciences
Radiance field methods, while achieving impressive quality in novel view synthesis, require abundant input views. In the few-shot setting, both Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) are highly susceptible to overfitting to the ...
Jun Peng, Chunyi Chen, Yunbiao Liu
doaj   +1 more source

Multispectral NeRF : modeling real scenes and synthetic remote sensing imagery [PDF]

This project explores the use of Neural Radiance Fields (NeRF) in the multispectral domain. We build a NeRF model that supports multi-band images other than RGB.
Marcos Almansa, Arnau, Universitat Autònoma de Barcelona. Escola d'Enginyeria   +1 more
core  

NerfAcc: Efficient Sampling Accelerates NeRFs

, 2023
Optimizing and rendering Neural Radiance Fields is computationally expensive due to the vast number of samples required by volume rendering. Recent works have included alternative sampling approaches to help accelerate their methods, however, they are ...
Gao, Hang, Kanazawa, Angjoo, Li, Ruilong, Tancik, Matthew   +3 more
core  

Neural radiance fields-based holography [Invited]

This study presents a novel approach for generating holograms based on the neural radiance fields (NeRF) technique. Generating three-dimensional (3D) data is difficult in hologram computation.
Ito, Tomoyoshi, Kang, Minsung, Kumano, Kai, Shimobaba, Tomoyoshi, Wang, Fan   +4 more
core  

Survey on Controlable Image Synthesis with Deep Learning

, 2023
Image synthesis has attracted emerging research interests in academic and industry communities. Deep learning technologies especially the generative models greatly inspired controllable image synthesis approaches and applications, which aim to generate ...
Li, Jiao, Yang, Lu, Zhang, Shixiong
core  

Sat-DN: Implicit Surface Reconstruction From Multiview Satellite Images With Depth and Normal Supervision

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
With the advancement of satellite imaging technology, acquiring high-resolution multiview satellite imagery has become increasingly accessible, enabling efficient and location-independent ground model reconstruction.
Tianle Liu, Shuangming Zhao, Wanshou Jiang, Bingxuan Guo   +3 more
doaj   +1 more source

ZS-SRT: An Efficient Zero-Shot Super-Resolution Training Method for Neural Radiance Fields

, 2023
Neural Radiance Fields (NeRF) have achieved great success in the task of synthesizing novel views that preserve the same resolution as the training views. However, it is challenging for NeRF to synthesize high-quality high-resolution novel views with low-
Ding, Jiajun, Fan, Jianping, Feng, Xiang, He, Yongbo, Kuang, Zhenzhong, Qin, Feiwei, Wang, Chengkai, Wang, Yubo, Yu, Jun   +8 more
core  

NeRF-RE: An Improved Neural Radiance Field Model Based on Object Removal and Efficient Reconstruction

Information
High-quality green gardens can markedly enhance the quality of life and mental well-being of their users. However, health and lifestyle constraints make it difficult for people to enjoy urban gardens, and traditional methods struggle to offer the high ...
Ziyang Li, Yongjian Huai, Qingkuo Meng, Shiquan Dong   +3 more
doaj   +1 more source