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A benchmark dataset for objective quality assessment of view synthesis for neural radiance field (NeRF)Figshare [PDF]
Data in BriefNeural 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 +5 more
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Research on 3D reconstruction technology of large‐scale substation equipment based on NeRF
IET Science, Measurement and Technology, 2023 The high‐quality 3D model is the key to digital twin and visualization. Here, the neural radiation field (NeRF) is applied to greatly improve the speed and accuracy of 3D reconstruction of large‐scale substation equipment.
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MBS-NeRF: reconstruction of sharp neural radiance fields from motion-blurred sparse images [PDF]
Scientific ReportsThe 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 +3 more
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Multispectral-NeRF: A Multispectral Modeling Approach Based on Neural Radiance Fields [PDF]
Applied Sciences3D reconstruction technology generates three-dimensional representations of real-world objects, scenes, or environments using sensor data such as 2D images, with extensive applications in robotics, autonomous vehicles, and virtual reality systems ...
Hong Zhang +3 more
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Geo-Spatial Information ScienceTrue Digital Orthophoto Maps (TDOMs) have high geometric accuracy and rich image characteristics, making them essential geographic data for national economic and social development.
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SPARSESAT-NERF: DENSE DEPTH SUPERVISED NEURAL RADIANCE FIELDS FOR SPARSE SATELLITE IMAGES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 Digital surface model generation using traditional multi-view stereo matching (MVS) performs poorly over non-Lambertian surfaces, with asynchronous acquisitions, or at discontinuities. Neural radiance fields (NeRF) offer a new paradigm for reconstructing
L. Zhang, L. Zhang, E. Rupnik
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BRDF-NeRF: Neural radiance fields with optical satellite images and BRDF modelling
International Journal of Applied Earth Observations and GeoinformationNeural radiance fields (NeRF) have gained prominence as a machine learning technique for representing 3D scenes and estimating the bidirectional reflectance distribution function (BRDF) from multiple images. However, most existing research has focused on
Lulin Zhang +4 more
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Recursive-NeRF: An Efficient and Dynamically Growing NeRF
IEEE Transactions on Visualization and Computer Graphics, 2023 View synthesis methods using implicit continuous shape representations learned from a set of images, such as the Neural Radiance Field (NeRF) method, have gained increasing attention due to their high quality imagery and scalability to high resolution. However, the heavy computation required by its volumetric approach prevents NeRF from being useful in
Guo-Wei Yang +5 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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Frontiers in Behavioral Neuroscience, 2020 Memories of past events and common knowledge are critical to flexibly adjust one’s future behavior based on prior experiences. The formation and the transformation of these memories into a long-lasting form are supported by a dialogue between populations
Frédéric Michon +10 more
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