Results 41 to 50 of about 14,095 (277)
Neural Radiance Fields with Hash-Low-Rank Decomposition
Applied SciencesIn recent advancements in novel view synthesis and neural rendering, neural radiance field (NeRF) has emerged as a powerful technique for synthesizing high-quality novel views of complex 3D scenes.
Jiaxin Wang +3 more
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Multi-time-horizon Solar Forecasting Using Recurrent Neural Network
, 2018 The non-stationarity characteristic of the solar power renders traditional point forecasting methods to be less useful due to large prediction errors.
Mishra, Sakshi, Palanisamy, Praveen
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Initial Experiments on the Use of Radiance Fields for Underwater 3D Reconstruction [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesUnderwater photogrammetry presents unique challenges, including light attenuation, refraction, and turbidity, that affect the accuracy and quality of 3D reconstructions. This study investigates the performance of novel neural rendering techniques, Neural
B. Tanduo, F. Matrone, A. Murtiyoso
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MaRF: Representing Mars as Neural Radiance Fields
, 2023 The aim of this work is to introduce MaRF, a novel framework able to synthesize the Martian environment using several collections of images from rover cameras. The idea is to generate a 3D scene of Mars' surface to address key challenges in planetary surface exploration such as: planetary geology, simulated navigation and shape analysis. Although there
Giusti, Lorenzo +5 more
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Plenoxels: Radiance Fields without Neural Networks
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 For video and code, please see https://alexyu.net ...
Yu, Alex +5 more
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NeRFlex: Flexible Neural Radiance Fields With Diffeomorphic Deformation
IEEE AccessDue 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
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Light Field Super-Resolution Via Graph-Based Regularization
, 2017 Light field cameras capture the 3D information in a scene with a single exposure. This special feature makes light field cameras very appealing for a variety of applications: from post-capture refocus, to depth estimation and image-based rendering ...
Frossard, Pascal, Rossi, Mattia
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Removing Objects From Neural Radiance Fields
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 Neural Radiance Fields (NeRFs) are emerging as a ubiquitous scene representation that allows for novel view synthesis. Increasingly, NeRFs will be shareable with other people. Before sharing a NeRF, though, it might be desirable to remove personal information or unsightly objects.
Weder, Silvan +6 more
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Proceedings of the International Conference on Applied Innovations in IT, 2023 This paper addresses the problem of novel view synthesis using Neural Radiance Fields (NeRF) for scenes with dynamic illumination. NeRF training utilizes photometric consistency loss that is pixel-wise consistency between a set of scene images and ...
Olena Kolodiazhna +3 more
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VMRF: View Matching Neural Radiance Fields
Proceedings of the 30th ACM International Conference on Multimedia, 2022 Neural Radiance Fields (NeRF) have demonstrated very impressive performance in novel view synthesis via implicitly modelling 3D representations from multi-view 2D images. However, most existing studies train NeRF models with either reasonable camera pose initialization or manually-crafted camera pose distributions which are often unavailable or hard to
Zhang, Jiahui +7 more
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