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02/19/2023
Guided Depth Map Super-resolution: A Survey
Guided depth map super-resolution (GDSR), which aims to reconstruct a hi...
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09/09/2022
A Memory-Related Multi-Task Method Based on Task-Agnostic Exploration
We pose a new question: Can agents learn how to combine actions from pre...
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08/03/2022
Fast Hierarchical Deep Unfolding Network for Image Compressed Sensing
By integrating certain optimization solvers with deep neural network, de...
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12/13/2021
Deep Attentional Guided Image Filtering
Guided filter is a fundamental tool in computer vision and computer grap...
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12/07/2021
Image Compressed Sensing Using Non-local Neural Network
Deep network-based image Compressed Sensing (CS) has attracted much atte...
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06/10/2021
Data Clustering-Driven Neural Network for Intra Prediction
As a crucial part of video compression, intra prediction utilizes local ...
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04/04/2021
High-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal Fusion
Depth map records distance between the viewpoint and objects in the scen...
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01/06/2021
Multi-Stage Residual Hiding for Image-into-Audio Steganography
The widespread application of audio communication technologies has speed...
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03/10/2019
NormalNet: Learning based Guided Normal Filtering for Mesh Denoising
Mesh denoising is a critical technology in geometry processing, which ai...
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08/17/2018
Convolutional Neural Networks based Intra Prediction for HEVC
Traditional intra prediction methods for HEVC rely on using the nearest ...
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06/19/2018
Deep neural network based sparse measurement matrix for image compressed sensing
Gaussian random matrix (GRM) has been widely used to generate linear mea...
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04/13/2018
An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratios
The compressed sensing (CS) has been successfully applied to image compr...
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03/15/2018
A nonlinear transform based analog video transmission framework
Soft-cast, a cross-layer design for wireless video transmission, is prop...
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08/02/2017
An End-to-End Compression Framework Based on Convolutional Neural Networks
Deep learning, e.g., convolutional neural networks (CNNs), has achieved ...
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07/22/2017
Single Image Super-Resolution with Dilated Convolution based Multi-Scale Information Learning Inception Module
Traditional works have shown that patches in a natural image tend to red...
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07/22/2017
Deep Networks for Compressed Image Sensing
The compressed sensing (CS) theory has been successfully applied to imag...
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03/30/2017
Learning Convolutional Networks for Content-weighted Image Compression
Lossy image compression is generally formulated as a joint rate-distorti...
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07/07/2016
Random Walk Graph Laplacian based Smoothness Prior for Soft Decoding of JPEG Images
Given the prevalence of JPEG compressed images, optimizing image reconst...
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05/14/2014
Group-based Sparse Representation for Image Restoration
Traditional patch-based sparse representation modeling of natural images...
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05/11/2014
Image Restoration Using Joint Statistical Modeling in Space-Transform Domain
This paper presents a novel strategy for high-fidelity image restoration...
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04/30/2014
Image Compressive Sensing Recovery Using Adaptively Learned Sparsifying Basis via L0 Minimization
From many fewer acquired measurements than suggested by the Nyquist samp...
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04/29/2014
Structural Group Sparse Representation for Image Compressive Sensing Recovery
Compressive Sensing (CS) theory shows that a signal can be decoded from ...
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04/29/2014
Spatially Directional Predictive Coding for Block-based Compressive Sensing of Natural Images
A novel coding strategy for block-based compressive sens-ing named spati...
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12/25/2012
High Quality Image Interpolation via Local Autoregressive and Nonlocal 3-D Sparse Regularization
In this paper, we propose a novel image interpolation algorithm, which i...
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08/18/2012
Image Super-Resolution via Dual-Dictionary Learning And Sparse Representation
Learning-based image super-resolution aims to reconstruct high-frequency...
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08/18/2012