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08/10/2023
Critical Points ++: An Agile Point Cloud Importance Measure for Robust Classification, Adversarial Defense and Explainable AI
The ability to cope accurately and fast with Out-Of-Distribution (OOD) s...
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08/08/2023
Minimizing Quotient Regularization Model
Quotient regularization models (QRMs) are a class of powerful regulariza...
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05/04/2023
Additive Class Distinction Maps using Branched-GANs
We present a new model, training procedure and architecture to create pr...
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03/20/2023
EPiC: Ensemble of Partial Point Clouds for Robust Classification
Robust point cloud classification is crucial for real-world applications...
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01/12/2023
Graph Laplacian for Semi-Supervised Learning
Semi-supervised learning is highly useful in common scenarios where labe...
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12/18/2022
The Underlying Correlated Dynamics in Neural Training
Training of neural networks is a computationally intensive task. The sig...
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11/30/2022
BASiS: Batch Aligned Spectral Embedding Space
Graph is a highly generic and diverse representation, suitable for almos...
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09/15/2022
Spectral Total-Variation Processing of Shapes – Theory and Applications
In this work we present a comprehensive analysis of total variation (TV)...
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06/12/2022
Analysis of Branch Specialization and its Application in Image Decomposition
Branched neural networks have been used extensively for a variety of tas...
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05/20/2022
How to Guide Adaptive Depth Sampling?
Recent advances in depth sensing technologies allow fast electronic mane...
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11/21/2021
A Pseudo-Inverse for Nonlinear Operators
The Moore-Penrose inverse is widely used in physics, statistics and vari...
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12/17/2020
Experts with Lower-Bounded Loss Feedback: A Unifying Framework
The most prominent feedback models for the best expert problem are the f...
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10/06/2020
Iterative Methods for Computing Eigenvectors of Nonlinear Operators
In this chapter we are examining several iterative methods for solving n...
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07/27/2020
Adaptive LiDAR Sampling and Depth Completion using Ensemble Variance
This work considers the problem of depth completion, with or without ima...
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07/03/2020
Mode Decomposition for Homogeneous Symmetric Operators
Finding latent structures in data is drawing increasing attention in div...
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06/17/2020
Deeply Learned Spectral Total Variation Decomposition
Non-linear spectral decompositions of images based on one-homogeneous fu...
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01/11/2020
Unsupervised Enhancement of Real-World Depth Images Using Tri-Cycle GAN
Low quality depth poses a considerable challenge to computer vision algo...
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11/28/2019
Self-Supervised Unconstrained Illumination Invariant Representation
We propose a new and completely data-driven approach for generating an u...
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09/12/2019
Numeric Solutions of Eigenvalue Problems for Generic Nonlinear Operators
Numerical methods for solving linear eigenvalue problem are widely studi...
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08/04/2019
Image-Guided Depth Sampling and Reconstruction
Depth acquisition, based on active illumination, is essential for autono...
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03/23/2017
Nonlinear Spectral Image Fusion
In this paper we demonstrate that the framework of nonlinear spectral de...
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09/27/2016
Blind Facial Image Quality Enhancement using Non-Rigid Semantic Patches
We propose to combine semantic data and registration algorithms to solve...
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09/27/2016
Flows Generating Nonlinear Eigenfunctions
Nonlinear variational methods have become very powerful tools for many i...
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10/05/2015