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Found 20 papers, 1 papers with code
Multi-Band Wi-Fi Neural Dynamic Fusion
In contrast, this paper considers asynchronous sequence-to-sequence fusion between sub-7-GHz channel state information (CSI) and 60-GHz beam signal-to-noise-ratio~(SNR)s for more challenging tasks such as continuous coordinate estimation.
Physics-Informed Koopman Network
Koopman operator theory is receiving increased attention due to its promise to linearize nonlinear dynamics.
Fast and High-Quality Blind Multi-Spectral Image Pansharpening
First, we estimate the blur kernel by computing the kernel coefficients with minimum total generalized variation that blur a downsampled version of the PAN image to approximate a linear combination of the LRMS image channels.
Multiview Sensing With Unknown Permutations: An Optimal Transport Approach
In several applications, including imaging of deformable objects while in motion, simultaneous localization and mapping, and unlabeled sensing, we encounter the problem of recovering a signal that is measured subject to unknown permutations.
High-Contrast Reflection Tomography with Total-Variation Constraints
Inverse scattering is the process of estimating the spatial distribution of the scattering potential of an object by measuring the scattered wavefields around it.
Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation
In order to impute the missing values, state-of-the-art methods are built on Recurrent Neural Networks (RNN), which process each time stamp sequentially, prohibiting the direct modeling of the relationship between distant time stamps.
Graph Based Skeleton Modeling for Human Activity Analysis
Understanding human activity based on sensor information is required in many applications and has been an active research area.
Ranked #4 on
Skeleton Based Action Recognition
on MSR Action3D
On the modes of convergence of Stochastic Optimistic Mirror Descent (OMD) for saddle point problems
In this article, we study the convergence of Mirror Descent (MD) and Optimistic Mirror Descent (OMD) for saddle point problems satisfying the notion of coherence as proposed in Mertikopoulos et al. We prove convergence of OMD with exact gradients for coherent saddle point problems, and show that monotone convergence only occurs after some sufficiently large number of iterations.
CDSA: Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation
In order to jointly capture the self-attention across multiple dimensions, including time, location and the sensor measurements, while maintain low computational complexity, we propose a novel approach called Cross-Dimensional Self-Attention (CDSA) to process each dimension sequentially, yet in an order-independent manner.
Sparse Blind Deconvolution for Distributed Radar Autofocus Imaging
Common techniques that attempt to resolve the antenna ambiguity generally assume an unknown gain and phase error afflicting the radar measurements.
Online Detection of Action Start in Untrimmed, Streaming Videos
We aim to tackle a novel task in action detection - Online Detection of Action Start (ODAS) in untrimmed, streaming videos.
Accelerated Image Reconstruction for Nonlinear Diffractive Imaging
The problem of reconstructing an object from the measurements of the light it scatters is common in numerous imaging applications.
SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering
Specifically, it corresponds to a series expansion of the scattered wave with an accelerated-gradient method.
Guided Signal Reconstruction Theory
New frame-less reconstruction methods are proposed, based on a novel concept of a reconstruction set, defined as a shortest pathway between the sample consistent set and the guiding set.
Compressive Imaging with Iterative Forward Models
We propose a new compressive imaging method for reconstructing 2D or 3D objects from their scattered wave-field measurements.
A Recursive Born Approach to Nonlinear Inverse Scattering
The Iterative Born Approximation (IBA) is a well-known method for describing waves scattered by semi-transparent objects.
Representation and Coding of Signal Geometry
In this paper, we examine the problem of encoding signals such that sufficient information is preserved about their pairwise distances and their inner products.
Learning optimal nonlinearities for iterative thresholding algorithms
Iterative shrinkage/thresholding algorithm (ISTA) is a well-studied method for finding sparse solutions to ill-posed inverse problems.
Chebyshev and Conjugate Gradient Filters for Graph Image Denoising
In 3D image/video acquisition, different views are often captured with varying noise levels across the views.
Fast methods for denoising matrix completion formulations, with applications to robust seismic data interpolation
In this paper, we consider matrix completion formulations designed to hit a target data-fitting error level provided by the user, and propose an algorithm called LR-BPDN that is able to exploit factorized formulations to solve the corresponding optimization problem.
