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Light field angular super resolution based on residual channel attention and classification up-sampling
Current light field angular super resolution algorithms generate coarse viewpoint images due to their low learning ability and equally upsample all...
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MFSRNet: spatial-angular correlation retaining for light field super-resolution
Light field (LF) images acquired by hand-held devices suffer from a trade-off between spatial and angular resolutions. To solve this problem,...
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Spatial-Angular Decoupling Interaction Networks for Light Field Angular Super-Resolution
The light field image simultaneously captures both the intensity and directional information of light rays, making it a valuable tool for acquiring...
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Light field angular super-resolution based on structure and scene information
Light fields contain a wealth of information about real-world scenes and can be easily acquired by commercial light field cameras. However, the...
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Light Field Angular Super-Resolution via Dense Correspondence Field Reconstruction
Light field (LF) angular super-resolution (SR) aims at reconstructing a densely sampled LF from a sparsely sampled one. To achieve accurate angular...
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Light Field Image Super-Resolution via Global-View Information Adaption and Angular Attention Fusion
Light field (LF) is a emerging technology, which can be used in many fields. Furthermore, LF cameras can capture spatial and angular information of...
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Spatio-Angular Resolution Trade-Off in Face Recognition
Ensuring robustness in face recognition systems across various challenging conditions is crucial for their versatility. State-of-the-art methods...
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Light field super-resolution using complementary-view feature attention
Light field (LF) cameras record multiple perspectives by a sparse sampling of real scenes, and these perspectives provide complementary information....
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Direct Inter-Intra View Association for Light Field Super-Resolution
Light field (LF) cameras record both intensity and directions of light rays in a scene with a single exposure. However, due to the inevitable...
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Depth-guided learning light field angular super-resolution with edge-aware inpainting
High angular resolution light field (LF) enables exciting applications such as depth estimation, virtual reality, and augmented reality. Although...
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Exploiting local detail in single image super-resolution via hypergraph convolution
Exploiting both local detail features and global correlation information in low-resolution (LR) images is vital for single-image super-resolution...
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Lightweight network with masks for light field image super-resolution based on swin attention
Light field (LF) image super-resolution (SR) is a technique designed to enhance the details and clarity of low-resolution (LR) light field images by...
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ZEPI-Net: Light Field Super Resolution via Internal Cross-Scale Epipolar Plane Image Zero-Shot Learning
Many applications of light field (LF) imaging have been limited by the spatial-angular resolution problem, hence the need for efficient...
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Downsampling consistency correction-based quality enhancement for CNN-based light field image super-resolution
In recent years, numerous CNN-based light field (LF) image super-resolution (SR) methods have been developed. However, due to the downsampling...
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A Coarse-to-Fine Convolutional Neural Network for Light Field Angular Super-Resolution
Densely-sampled light field (LF) images are drawing increasing attention for their wide applications, such as 3D reconstruction, virtual reality, and...
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Deep-Based Super-Angular Resolution for Diffusion Imaging
High angular resolution diffusion imaging (HARDI) allows for more detailed fiber structures to be obtained by scanning in more directions than...
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HighBoostNet: a deep light-weight image super-resolution network using high-boost residual blocks
Image distortion is an inevitable part of the image acquisition process, which negatively affects the high-frequency contents of the images....
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Light Field Super-Resolution Based on Spatial and Angular Attention
Light field (LF) images captured by LF cameras can store the intensity and direction information of light rays in the scene, which have advantages in...
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MPIN: a macro-pixel integration network for light field super-resolution
Most existing light field (LF) super-resolution (SR) methods either fail to fully use angular information or have an unbalanced performance...
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Hierarchical feature fusion network for light field spatial super-resolution
Light field (LF) spatial super-resolution (SR) aims to restore a high-resolution LF image from a degraded low-resolution one. However, due to the...
