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Lfnat 2023 challenge on light field depth estimation: Methods and results
This paper reviews the 1st LFNAT challenge on light field depth estimation, which aims at
predicting disparity information of central view image in a light field (ie, pixel offset between …
predicting disparity information of central view image in a light field (ie, pixel offset between …
Exploiting spatial and angular correlations with deep efficient transformers for light field image super-resolution
Global context information is particularly important for comprehensive scene understanding.
It helps clarify local confusions and smooth predictions to achieve fine-grained and coherent …
It helps clarify local confusions and smooth predictions to achieve fine-grained and coherent …
NTIRE 2024 challenge on light field image super-resolution: Methods and results
In this report we summarize the 2nd NTIRE challenge on light field (LF) image super-
resolution (SR) with a focus on new methods and results. This challenge aims at super …
resolution (SR) with a focus on new methods and results. This challenge aims at super …
Learning non-local spatial-angular correlation for light field image super-resolution
Exploiting spatial-angular correlation is crucial to light field (LF) image super-resolution
(SR), but is highly challenging due to its non-local property caused by the disparities among …
(SR), but is highly challenging due to its non-local property caused by the disparities among …
NTIRE 2023 challenge on light field image super-resolution: Dataset, methods and results
In this report, we summarize the first NTIRE challenge on light field (LF) image super-
resolution (SR), which aims at super-resolving LF images under the standard bicubic …
resolution (SR), which aims at super-resolving LF images under the standard bicubic …
LFRSNet: A robust light field semantic segmentation network combining contextual and geometric features
Light field (LF) semantic segmentation is a newly arisen technology and is widely used in
many smart city applications such as remote sensing, virtual reality and 3D photogrammetry …
many smart city applications such as remote sensing, virtual reality and 3D photogrammetry …
Cross-view recurrence-based self-supervised super-resolution of light field
Compared with external-supervised learning-based (ESLB) methods, self-supervised
learning-based (SSLB) methods can overcome the domain gap problem caused by different …
learning-based (SSLB) methods can overcome the domain gap problem caused by different …
Light field depth estimation for non-lambertian objects via adaptive cross operator
Light field (LF) depth estimation is a crucial basis for LF-related applications. Most existing
methods are based on the Lambertian assumption and cannot deal with non-Lambertian …
methods are based on the Lambertian assumption and cannot deal with non-Lambertian …
Cutmib: Boosting light field super-resolution via multi-view image blending
Data augmentation (DA) is an efficient strategy for improving the performance of deep neural
networks. Recent DA strategies have demonstrated utility in single image super-resolution …
networks. Recent DA strategies have demonstrated utility in single image super-resolution …
[HTML][HTML] A survey for light field super-resolution
Compared to 2D imaging data, the 4D light field (LF) data retains richer scene's structure
information, which can significantly improve the computer's perception capability, including …
information, which can significantly improve the computer's perception capability, including …