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Physics-based Shadow Image Decomposition for Shadow Removal
We propose a novel deep learning method for shadow removal. Inspired by ...
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Modeling Deep Learning Based Privacy Attacks on Physical Mail
Mail privacy protection aims to prevent unauthorized access to hidden co...
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FaceDet3D: Facial Expressions with 3D Geometric Detail Prediction
Facial Expressions induce a variety of high-level details on the 3D face...
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Intrinsic Decomposition of Document Images In-the-Wild
Automatic document content processing is affected by artifacts caused by...
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Variational Transfer Learning for Fine-grained Few-shot Visual Recognition
Fine-grained few-shot recognition often suffers from the problem of trai...
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Learning Clusterable Visual Features for Zero-Shot Recognition
In zero-shot learning (ZSL), conditional generators have been widely use...
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Distribution Matching for Crowd Counting
In crowd counting, each training image contains multiple people, where e...
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Light Direction and Color Estimation from Single Image with Deep Regression
We present a method to estimate the direction and color of the scene lig...
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A Study of Human Gaze Behavior During Visual Crowd Counting
In this paper, we describe our study on how humans allocate their attent...
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From Shadow Segmentation to Shadow Removal
The requirement for paired shadow and shadow-free images limits the size...
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Predicting Goal-directed Human Attention Using Inverse Reinforcement Learning
Being able to predict human gaze behavior has obvious importance for beh...
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Towards Better Opioid Antagonists Using Deep Reinforcement Learning
Naloxone, an opioid antagonist, has been widely used to save lives from ...
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Dataset of Segmented Nuclei in Hematoxylin and Eosin Stained Histopathology Images of 10 Cancer Types
The distribution and appearance of nuclei are essential markers for the ...
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Self-supervised Deformation Modeling for Facial Expression Editing
Recent advances in deep generative models have demonstrated impressive r...
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Exascale Deep Learning to Accelerate Cancer Research
Deep learning, through the use of neural networks, has demonstrated rema...
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Shadow Removal via Shadow Image Decomposition
We propose a novel deep learning method for shadow removal. Inspired by ...
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Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types
Deep learning classifiers for characterization of whole slide tissue mor...
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Topology-Preserving Deep Image Segmentation
Segmentation algorithms are prone to make topological errors on fine-sca...
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Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer
Quantitative assessment of Tumor-TIL spatial relationships is increasing...
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Weakly Labeling the Antarctic: The Penguin Colony Case
Antarctic penguins are important ecological indicators -- especially in ...
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Lifting AutoEncoders: Unsupervised Learning of a Fully-Disentangled 3D Morphable Model using Deep Non-Rigid Structure from Motion
In this work we introduce Lifting Autoencoders, a generative 3D surface-...
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Label Super Resolution with Inter-Instance Loss
For the task of semantic segmentation, high-resolution (pixel-level) gro...
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Latent Space Optimal Transport for Generative Models
Variational Auto-Encoders enforce their learned intermediate latent-spac...
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Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance
In this work we introduce Deforming Autoencoders, a generative model for...
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Unsupervised Histopathology Image Synthesis
Hematoxylin and Eosin stained histopathology image analysis is essential...
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A+D-Net: Shadow Detection with Adversarial Shadow Attenuation
Single image shadow detection is a very challenging problem because of t...
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An Adversarial Neuro-Tensorial Approach For Learning Disentangled Representations
Several factors contribute to the appearance of an object in a visual sc...
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Improving Heterogeneous Face Recognition with Conditional Adversarial Networks
Heterogeneous face recognition between color image and depth image is a ...
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Sparse Autoencoder for Unsupervised Nucleus Detection and Representation in Histopathology Images
Histopathology images are crucial to the study of complex diseases such ...
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Geodesic Distance Histogram Feature for Video Segmentation
This paper proposes a geodesic-distance-based feature that encodes globa...
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Center-Focusing Multi-task CNN with Injected Features for Classification of Glioma Nuclear Images
Classifying the various shapes and attributes of a glioma cell nucleus i...
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Co-localization with Category-Consistent CNN Features and Geodesic Distance Propagation
Co-localization is the problem of localizing objects of the same class u...
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Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example
Resting-state functional Magnetic Resonance Imaging (R-fMRI) holds the p...
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Squared Earth Mover's Distance-based Loss for Training Deep Neural Networks
In the context of single-label classification, despite the huge success ...
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Neural Networks with Smooth Adaptive Activation Functions for Regression
In Neural Networks (NN), Adaptive Activation Functions (AAF) have parame...
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Patch-based Convolutional Neural Network for Whole Slide Tissue Image Classification
Convolutional Neural Networks (CNN) are state-of-the-art models for many...
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Region segmentation for sparse decompositions: better brain parcellations from rest fMRI
Functional Magnetic Resonance Images acquired during resting-state provi...
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On the Statistical Efficiency of ℓ_1,p Multi-Task Learning of Gaussian Graphical Models
In this paper, we present ℓ_1,p multi-task structure learning for Gaussi...
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