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Found 10 papers, 4 papers with code
Direct May Not Be the Best: An Incremental Evolution View of Pose Generation
Pose diversity is an inherent representative characteristic of 2D images.
MRC-Net: 6-DoF Pose Estimation with MultiScale Residual Correlation
Connecting the two stages is a novel multi-scale residual correlation (MRC) layer that captures high-and-low level correspondences between the input image and rendering from first stage.
Deep, convergent, unrolled half-quadratic splitting for image deconvolution
Through extensive experimental studies, we verify that our approach achieves competitive performance with state-of-the-art unrolled layer-specific learning and significantly improves over the traditional HQS algorithm.
Deep Algorithm Unrolling for Biomedical Imaging
In this chapter, we review biomedical applications and breakthroughs via leveraging algorithm unrolling, an important technique that bridges between traditional iterative algorithms and modern deep learning techniques.
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
In this article, we review algorithm unrolling for signal and image processing.
Robust Alignment for Panoramic Stitching via an Exact Rank Constraint
We study the problem of image alignment for panoramic stitching.
Deep Algorithm Unrolling for Blind Image Deblurring
We then unroll the algorithm to construct a neural network for image deblurring which we refer to as Deep Unrolling for Blind Deblurring (DUBLID).
An Algorithm Unrolling Approach to Deep Image Deblurring
We first present an iterative algorithm that may be considered a generalization of the traditional total-variation regularization method on the gradient domain, and subsequently unroll the half-quadratic splitting algorithm to construct a neural network.
Blind Image Deblurring Using Row-Column Sparse Representations
Blind image deblurring is a particularly challenging inverse problem where the blur kernel is unknown and must be estimated en route to recover the deblurred image.
A Maximum A Posteriori Estimation Framework for Robust High Dynamic Range Video Synthesis
For HDR video, a stiff practical challenge presents itself in the form of accurate correspondence estimation of objects between video frames.
