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07/21/2023
YOLOPose V2: Understanding and Improving Transformer-based 6D Pose Estimation
6D object pose estimation is a crucial prerequisite for autonomous robot...
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02/06/2023
RoboCup 2022 AdultSize Winner NimbRo: Upgraded Perception, Capture Steps Gait and Phase-based In-walk Kicks
Beating the human world champions by 2050 is an ambitious goal of the Hu...
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11/20/2022
Learning Nonlinear Couplings in Network of Agents from a Single Sample Trajectory
We consider a class of stochastic dynamical networks whose governing dyn...
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05/05/2022
YOLOPose: Transformer-based Multi-Object 6D Pose Estimation using Keypoint Regression
6D object pose estimation is a crucial prerequisite for autonomous robot...
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03/10/2022
Robustness Analysis of Classification Using Recurrent Neural Networks with Perturbed Sequential Input
For a given stable recurrent neural network (RNN) that is trained to per...
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03/04/2022
Bayesian community detection for networks with covariates
The increasing prevalence of network data in a vast variety of fields an...
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02/21/2022
Two-snapshot DOA Estimation via Hankel-structured Matrix Completion
In this paper, we study the problem of estimating the direction of arriv...
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09/22/2021
T6D-Direct: Transformers for Multi-Object 6D Pose Direct Regression
6D pose estimation is the task of predicting the translation and orienta...
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07/06/2021
Real-time Pose Estimation from Images for Multiple Humanoid Robots
Pose estimation commonly refers to computer vision methods that recogniz...
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05/03/2021
Robust Learning of Recurrent Neural Networks in Presence of Exogenous Noise
Recurrent Neural networks (RNN) have shown promising potential for learn...
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12/18/2020
Distributed Map Classification using Local Observations
We consider the problem of classifying a map using a team of communicati...
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01/12/2020
On the Compressibility of Affinely Singular Random Vectors
There are several ways to measure the compressibility of a random measur...
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09/08/2019
Living near the edge: A lower-bound on the phase transition of total variation minimization
This work is about the total variation (TV) minimization which is used f...
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09/27/2018
Optimal Exploitation of Subspace Prior Information in Matrix Sensing
Matrix sensing is the problem of reconstructing a low-rank matrix from a...
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09/09/2018
Distribution-aware Block-sparse Recovery via Convex Optimization
We study the problem of reconstructing a block-sparse signal from compre...
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08/13/2018
Improved Recovery of Analysis Sparse Vectors in Presence of Prior Information
In this work, we consider the problem of recovering analysis-sparse sign...
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08/13/2018
Eigenvectors of Deformed Wigner Random Matrices
We investigate eigenvectors of rank-one deformations of random matrices ...
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07/03/2018
Robustness of Two-Dimensional Line Spectral Estimation Against Spiky Noise
The aim of two-dimensional line spectral estimation is to super-resolve ...
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06/27/2018
On the Error in Phase Transition Computations for Compressed Sensing
Evaluating the statistical dimension is a common tool to determine the a...
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04/20/2018
Exploiting Prior Information in Block Sparse Signals
We study the problem of recovering a block-sparse signal from under-samp...
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03/08/2018
Sample Complexity of Total Variation Minimization
This work considers the use of Total variation (TV) minimization in the ...
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06/26/2016