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Disentangling light fields for super-resolution and disparity estimation
Light field (LF) cameras record both intensity and directions of light rays, and encode 3D
scenes into 4D LF images. Recently, many convolutional neural networks (CNNs) have …
scenes into 4D LF images. Recently, many convolutional neural networks (CNNs) have …
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 …
UrbanLF: A comprehensive light field dataset for semantic segmentation of urban scenes
As one of the fundamental technologies for scene understanding, semantic segmentation
has been widely explored in the last few years. Light field cameras encode the geometric …
has been widely explored in the last few years. Light field cameras encode the geometric …
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 …
Virtual-scanning light-field microscopy for robust snapshot high-resolution volumetric imaging
Abstract High-speed three-dimensional (3D) intravital imaging in animals is useful for
studying transient subcellular interactions and functions in health and disease. Light-field …
studying transient subcellular interactions and functions in health and disease. Light-field …
Detail-preserving transformer for light field image super-resolution
Recently, numerous algorithms have been developed to tackle the problem of light field
super-resolution (LFSR), ie, super-resolving low-resolution light fields to gain high …
super-resolution (LFSR), ie, super-resolving low-resolution light fields to gain high …
Occlusion-aware cost constructor for light field depth estimation
Matching cost construction is a key step in light field (LF) depth estimation, but was rarely
studied in the deep learning era. Recent deep learning-based LF depth estimation methods …
studied in the deep learning era. Recent deep learning-based LF depth estimation methods …
Light field image super-resolution with transformers
Light field (LF) image super-resolution (SR) aims at reconstructing high-resolution LF
images from their low-resolution counterparts. Although CNN-based methods have …
images from their low-resolution counterparts. Although CNN-based methods have …