
SalGaze: Personalizing Gaze Estimation Using Visual Saliency
Traditional gaze estimation methods typically require explicit user cali...
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Domaininvariant Learning using Adaptive Filter Decomposition
Domain shifts are frequently encountered in realworld scenarios. In thi...
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ScaleEquivariant Neural Networks with Decomposed Convolutional Filters
Encoding the input scale information explicitly into the representation ...
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Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors
Deep neural networks (DNNs) are notorious for their vulnerability to adv...
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Stochastic Conditional Generative Networks with Basis Decomposition
While generative adversarial networks (GANs) have revolutionized machine...
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Continuous Dice Coefficient: a Method for Evaluating Probabilistic Segmentations
Objective: Overlapping measures are often utilized to quantify the simil...
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Range Adaptation for 3D Object Detection in LiDAR
LiDARbased 3D object detection plays a crucial role in modern autonomou...
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ForestHash: Semantic Hashing With Shallow Random Forests and Tiny Convolutional Networks
Hash codes are efficient data representations for coping with the ever g...
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LDMNet: Low Dimensional Manifold Regularized Neural Networks
Deep neural networks have proved very successful on archetypal tasks for...
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Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems
Security, privacy, and fairness have become critical in the era of data ...
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Tradeoffs between Convergence Speed and Reconstruction Accuracy in Inverse Problems
Solving inverse problems with iterative algorithms is popular, especiall...
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Robust Large Margin Deep Neural Networks
The generalization error of deep neural networks via their classificatio...
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Deep Video Deblurring
Motion blur from camera shake is a major problem in videos captured by h...
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Selflearning Scenespecific Pedestrian Detectors using a Progressive Latent Model
In this paper, a selflearning approach is proposed towards solving scen...
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Not Afraid of the Dark: NIRVIS Face Recognition via Crossspectral Hallucination and Lowrank Embedding
Surveillance cameras today often capture NIR (near infrared) images in l...
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Probabilistic FluorescenceBased Synapse Detection
Brain function results from communication between neurons connected by c...
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Nonnegative Matrix Underapproximation for Robust Multiple Model Fitting
In this work, we introduce a highly efficient algorithm to address the n...
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Fast L1NMF for Multiple Parametric Model Estimation
In this work we introduce a comprehensive algorithmic pipeline for multi...
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Generalization Error of Invariant Classifiers
This paper studies the generalization error of invariant classifiers. In...
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Compressed Nonnegative Matrix Factorization is Fast and Accurate
Nonnegative matrix factorization (NMF) has an established reputation as ...
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Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?
Three important properties of a classification machinery are: (i) the sy...
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On the Stability of Deep Networks
In this work we study the properties of deep neural networks (DNN) with ...
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Fundamental Limits in Multiimage Alignment
The performance of multiimage alignment, bringing different images into...
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Dissimilaritybased Sparse Subset Selection
Finding an informative subset of a large collection of data points or mo...
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GraphConnect: A Regularization Framework for Neural Networks
Deep neural networks have proved very successful in domains where large ...
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Graph Matching: Relax at Your Own Risk
Graph matchingaligning a pair of graphs to minimize their edge disagr...
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Robust Multimodal Graph Matching: Sparse Coding Meets Graph Matching
Graph matching is a challenging problem with very important applications...
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Removing Camera Shake via Weighted Fourier Burst Accumulation
Numerous recent approaches attempt to remove image blur due to camera sh...
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Data Representation using the Weyl Transform
The Weyl transform is introduced as a rich framework for data representa...
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Random Forests Can Hash
Hash codes are a very efficient data representation needed to be able to...
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SemiSupervised Single and MultiDomain Regression with MultiDomain Training
We address the problems of multidomain and singledomain regression bas...
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An MDL framework for sparse coding and dictionary learning
The power of sparse signal modeling with learned overcomplete dictionar...
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Lowrank data modeling via the Minimum Description Length principle
Robust lowrank matrix estimation is a topic of increasing interest, wit...
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A Biclustering Framework for Consensus Problems
We consider grouping as a general characterization for problems such as ...
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A convex model for nonnegative matrix factorization and dimensionality reduction on physical space
A collaborative convex framework for factoring a data matrix X into a no...
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Learning Transformations for Classification Forests
This work introduces a transformationbased learner model for classifica...
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Sparse similaritypreserving hashing
In recent years, a lot of attention has been devoted to efficient neares...
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Learning Transformations for Clustering and Classification
A lowrank transformation learning framework for subspace clustering and...
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Domaininvariant Face Recognition using Learned Lowrank Transformation
We present a lowrank transformation approach to compensate for face var...
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Learning Robust Subspace Clustering
We propose a lowrank transformationlearning framework to robustify sub...
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Video Human Segmentation using Fuzzy Object Models and its Application to Body Pose Estimation of Toddlers for Behavior Studies
Video object segmentation is a challenging problem due to the presence o...
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Computer vision tools for the noninvasive assessment of autismrelated behavioral markers
The early detection of developmental disorders is key to child outcome, ...
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A Complete System for Candidate Polyps Detection in Virtual Colonoscopy
Computer tomographic colonography, combined with computeraided detectio...
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Are You Imitating Me? Unsupervised Sparse Modeling for Group Activity Analysis from a Single Video
A framework for unsupervised group activity analysis from a single video...
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Learning Efficient Structured Sparse Models
We present a comprehensive framework for structured sparse coding and mo...
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TaskDriven Adaptive Statistical Compressive Sensing of Gaussian Mixture Models
A framework for adaptive and nonadaptive statistical compressive sensin...
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Online Adaptive Statistical Compressed Sensing of Gaussian Mixture Models
A framework of online adaptive statistical compressed sensing is introdu...
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Statistical Compressed Sensing of Gaussian Mixture Models
A novel framework of compressed sensing, namely statistical compressed s...
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Collaborative Sources Identification in Mixed Signals via Hierarchical Sparse Modeling
A collaborative framework for detecting the different sources in mixed s...
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Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compress...
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Guillermo Sapiro
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Guillermo Sapiro is an informatics, electrical engineering and professor who has made a significant contribution to the processing of images. He worked for 15 years at the University of Minnesota before joining Duke University as a Professor. He has also researched image processing in Hewlett Packard Labs and is known for being one of the people who originally developed the LOCOI Compression Algorithm for image lossless compression. It also contributed significantly to the development of the Adobe After Effects rotobrush tool that has been included in the After Effects version since CS5. Adobe uses his research in a variety of projects such as Photoshop and hires his students often. He also teaches a massive open online course on image and video processing through Coursera. The title of the course is “Image and video processing: from Mars to Hollywood with a hospital stop.” He lives with his wife, the two sons and the golden Hummus recorder.