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Multi-sensor multispectral reconstruction framework based on projection and reconstruction
The scarcity and low spatial resolution of hyperspectral images (HSIs) have become a major problem limiting the application of the images. In recent...
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Coordinated Reconstruction Dual-Branch Network for Low-Dose PET Reconstruction
Positron Emission Tomography (PET), known for its sensitivity and non-invasiveness in visualizing metabolic processes in the human body, has been...
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Multi-view Stereo Reconstruction
This chapter discusses the problem of multi-view stereo reconstruction, which is the process of recovering the surface of an object from many images....
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Multi-View Euclidean Reconstruction
Given the pixel coordinates of the projections of 3D points in multiple images, we can find the 3D points and the camera matrices that satisfy the...
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InceptCurves: curve reconstruction using an inception network
Curve reconstruction is a fundamental task in many visual computing applications. In this paper, a data-driven approach for curve reconstruction is...
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A subdivision-based framework for shape reconstruction
Shape reconstruction from 3D point clouds is one of the most important topic in the field of computer graphics. In this paper, we propose a...
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Improving MRI reconstruction with graph search matching pursuit
Nowadays, magnetic resonance imaging (MRI) is the go-to method for safe and effective diagnosis in hospitals. However, it can be slow and costly due...
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Balanced reconstruction codes for single edits
Motivated by the sequence reconstruction problem initiated by Levenshtein, reconstruction codes were introduced by Cai et al. to combat errors when a...
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Multi-view Projective Reconstruction and Autocalibration
In this chapter, we will study the problem of computing a projective reconstruction from multiple uncalibrated images. We will describe a global...
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Contrastive local constraint for irregular image reconstruction and editability
GAN inversion aims to invert a real image back into the latent space of a pre-trained GAN model, showing great potential in image reconstruction and...
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Deep Cardiac MRI Reconstruction with ADMM
Cardiac magnetic resonance imaging (CMR) is a valuable non-invasive tool for identifying cardiovascular diseases. For instance, Cine MRI is the...
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Multi-object reconstruction of plankton digital holograms
Plankton is the base of the ocean ecosystem and is very sensitive to changes in their environment. Thus, monitoring the status of plankton in-situ ...
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Image manipulation localization using reconstruction attention
With the development of image manipulation techniques and the widespread use of image editing tools, it is effortless to forge images without leaving...
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Improved 3D human face reconstruction from 2D images using blended hard edges
This study reports an effective and robust edge-based scheme for the reconstruction of 3D human faces from input of single images, addressing...
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DAGM-Mono: Deformable Attention-Guided Modeling for Monocular 3D Reconstruction
AbstractAccurate 3D pose estimation and shape reconstruction from monocular images is a challenging task in the field of autonomous driving. Our work...
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Iterative shrinkage thresholding-based anti-multi-noise compression perceptual image reconstruction network
Telemedicine imaging services usually require wireless transmission of a large number of medical images MRI/CT, etc., in the network, which are...
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Adaptive deep learning network for image reconstruction of compressed sensing
In this paper, we study how to achieve sparse sampling and high-quality reconstruction of natural images, and propose an interpretable deep network...
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Personalizing human avatars based on realistic 3D facial reconstruction
Personalized 3D human avatars have aroused a great deal of interest because it is attractive to most people, particularly generation Z, to have the...
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References tracking and perturbations reconstruction in a Cartesian robot
An exosystem needs to be nonlinear when it generates the perturbations to be reconstructed; however, an exosystem does not need to be nonlinear when...
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A conditioned feature reconstruction network for few-shot classification
Few-shot classification is one of the most daunting challenges in deep learning. The complexities of this task arise from the fact that category...
