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SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image
[article]
2022
arXiv
pre-print
In this work, we consider a more ambitious task: training neural radiance field, over realistically complex visual scenes, by "looking only once", i.e., using only a single view. ...
Despite the rapid development of Neural Radiance Field (NeRF), the necessity of dense covers largely prohibits its wider applications. ...
Fig. 1 : Given only a single reference view as input, our novel semi-supervised framework trains a neural radiance field effectively. ...
arXiv:2204.00928v1
fatcat:26pkhk6gnbednjiyyxwv4j2uru
Ray Priors through Reprojection: Improving Neural Radiance Fields for Novel View Extrapolation
[article]
2022
arXiv
pre-print
Neural Radiance Fields (NeRF) have emerged as a potent paradigm for representing scenes and synthesizing photo-realistic images. ...
Furthermore, we show that a ray atlas pre-computed from the observed rays' viewing directions could further enhance the rendering quality for extrapolated views. ...
A good practice is from Neural Radiance Fields (NeRF) [22] . ...
arXiv:2205.05922v1
fatcat:irnlftnohfa5tf5lfem4ld7bj4
Machine Learning-Based View Synthesis in Fourier Lightfield Microscopy
2022
Sensors
In this context we investigate here the use of a neural radiance field view synthesis method, originally developed for its use with macroscopic scenes acquired with a moving (or an array of static) digital ...
Therefore, it is important to have a tool for the generation of a high number of synthesized view images, without compromising their lateral resolution. ...
In this sense, this paper presents, to the best of our knowledge, the first application of a neural radiance field-type method (NeRF--) for the synthesis of new views in FLMic. ...
doi:10.3390/s22093487
pmid:35591177
pmcid:PMC9099650
fatcat:nuqyq3m4yrg3nlcboj5fglxvba