
-
2D+3D Facial Expression Recognition via Discriminative Dynamic Range Enhancement and Multi-Scale Learning
In 2D+3D facial expression recognition (FER), existing methods generate ...
read it
-
EffiScene: Efficient Per-Pixel Rigidity Inference for Unsupervised Joint Learning of Optical Flow, Depth, Camera Pose and Motion Segmentation
This paper addresses the challenging unsupervised scene flow estimation ...
read it
-
Probabilistic Massive MIMO Channel Estimation with Built-in Parameter Estimation
In order to reduce hardware complexity and power consumption, massive mu...
read it
-
1-Bit Compressive Sensing via Approximate Message Passing with Built-in Parameter Estimation
1-bit compressive sensing aims to recover sparse signals from quantized ...
read it
-
A Scale Invariant Flatness Measure for Deep Network Minima
It has been empirically observed that the flatness of minima obtained fr...
read it
-
Reducing Sampling Ratios and Increasing Number of Estimates Improve Bagging in Sparse Regression
Bagging, a powerful ensemble method from machine learning, improves the ...
read it
-
Generative Adversarial Networks for Recovering Missing Spectral Information
Ultra-wideband (UWB) radar systems nowadays typical operate in the low f...
read it
-
JOBS: Joint-Sparse Optimization from Bootstrap Samples
Classical signal recovery based on ℓ_1 minimization solves the least squ...
read it
-
Adversarial Deep Structured Nets for Mass Segmentation from Mammograms
Mass segmentation provides effective morphological features which are im...
read it
-
Sparse Coding and Autoencoders
In "Dictionary Learning" one tries to recover incoherent matrices A^* ∈R...
read it
-
Automatic Vertebra Labeling in Large-Scale 3D CT using Deep Image-to-Image Network with Message Passing and Sparsity Regularization
Automatic localization and labeling of vertebra in 3D medical images pla...
read it
-
Regularizing Face Verification Nets For Pain Intensity Regression
Limited labeled data are available for the research of estimating facial...
read it
-
Supervised Deep Sparse Coding Networks
In this paper, we describe the deep sparse coding network (SCN), a novel...
read it
-
Linear Disentangled Representation Learning for Facial Actions
Limited annotated data available for the recognition of facial expressio...
read it
-
Adversarial Deep Structural Networks for Mammographic Mass Segmentation
Mass segmentation is an important task in mammogram analysis, providing ...
read it
-
Pose-Selective Max Pooling for Measuring Similarity
In this paper, we deal with two challenges for measuring the similarity ...
read it
-
Sparse Coding with Fast Image Alignment via Large Displacement Optical Flow
Sparse representation-based classifiers have shown outstanding accuracy ...
read it
-
ICR: Iterative Convex Refinement for Sparse Signal Recovery Using Spike and Slab Priors
In this letter, we address sparse signal recovery using spike and slab p...
read it
-
Task-Driven Dictionary Learning for Hyperspectral Image Classification with Structured Sparsity Constraints
Sparse representation models a signal as a linear combination of a small...
read it
-
Multi-task Image Classification via Collaborative, Hierarchical Spike-and-Slab Priors
Promising results have been achieved in image classification problems by...
read it
-
Collaborative Multi-sensor Classification via Sparsity-based Representation
In this paper, we propose a general collaborative sparse representation ...
read it
-
Hierarchical Sparse and Collaborative Low-Rank Representation for Emotion Recognition
In this paper, we design a Collaborative-Hierarchical Sparse and Low-Ran...
read it
-
Structured Dictionary Learning for Classification
Sparsity driven signal processing has gained tremendous popularity in th...
read it
-
Structured Priors for Sparse-Representation-Based Hyperspectral Image Classification
Pixel-wise classification, where each pixel is assigned to a predefined ...
read it
-
Discriminative Local Sparse Representations for Robust Face Recognition
A key recent advance in face recognition models a test face image as a s...
read it