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Partial Differential Equations is All You Need for Generating Neural Architectures – A Theory for Physical Artificial Intelligence Systems
In this work, we generalize the reaction-diffusion equation in statistic...
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Lidar and Camera Self-Calibration using CostVolume Network
In this paper, we propose a novel online self-calibration approach for L...
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Learning an Adaptive Model for Extreme Low-light Raw Image Processing
Low-light images suffer from severe noise and low illumination. Current ...
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NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
This paper reviews the NTIRE 2020 challenge on real image denoising with...
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Manifold Criterion Guided Transfer Learning via Intermediate Domain Generation
In many practical transfer learning scenarios, the feature distribution ...
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Universal, transferable and targeted adversarial attacks
Deep Neural Network has been found vulnerable in many previous works. A ...
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Optimized CNN for PolSAR Image Classification via Differentiable Neural Architecture Search
Convolutional neural networks (CNNs) realize the automation of feature e...
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Pyramid Feature Selective Network for Saliency detection
Saliency detection is one of the basic challenges in computer vision. Ho...
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Filter Grafting for Deep Neural Networks
This paper proposes a new learning paradigm called filter grafting, whic...
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Fuzzy Semantic Segmentation of Breast Ultrasound Image with Breast Anatomy Constraints
Breast cancer is one of the most serious disease affects women's health....
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Learning deep neural networks in blind deblurring framework
Recently, end-to-end learning methods based on deep neural network (DNN)...
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Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net
Hyperspectral imaging can help better understand the characteristics of ...
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TanhExp: A Smooth Activation Function with High Convergence Speed for Lightweight Neural Networks
Lightweight or mobile neural networks used for real-time computer vision...
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Hyperspectral Image Classification in the Presence of Noisy Labels
Label information plays an important role in supervised hyperspectral im...
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Learning Symmetry Consistent Deep CNNs for Face Completion
Deep convolutional networks (CNNs) have achieved great success in face c...
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AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
This paper introduces the real image Super-Resolution (SR) challenge tha...
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Meta3D: Single-View 3D Object Reconstruction from Shape Priors in Memory
3D shape reconstruction from a single-view RGB image is an ill-posed pro...
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Mutual Information Gradient Estimation for Representation Learning
Mutual Information (MI) plays an important role in representation learni...
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Correspondence Learning for Controllable Person Image Generation
We present a generative model for controllable person image synthesis,as...
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Learning Deep Multi-Level Similarity for Thermal Infrared Object Tracking
Existing deep Thermal InfraRed (TIR) trackers only use semantic features...
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Assembly of randomly placed parts realized by using only one robot arm with a general parallel-jaw gripper
In industry assembly lines, parts feeding machines are widely employed a...
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TCDesc: Learning Topology Consistent Descriptors
Triplet loss is widely used for learning local descriptors from image pa...
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Cross-Scale Internal Graph Neural Network for Image Super-Resolution
Non-local self-similarity in natural images has been well studied as an ...
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Neural Melody Composition from Lyrics
In this paper, we study a novel task that learns to compose music from n...
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Siamese Box Adaptive Network for Visual Tracking
Most of the existing trackers usually rely on either a multi-scale searc...
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Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery
Recently, single gray/RGB image super-resolution reconstruction task has...
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Learning Structural Graph Layouts and 3D Shapes for Long Span Bridges 3D Reconstruction
A learning-based 3D reconstruction method for long-span bridges is propo...
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Rapid Whole Slide Imaging via Learning-based Two-shot Virtual Autofocusing
Whole slide imaging (WSI) is an emerging technology for digital patholog...
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Shift-Net: Image Inpainting via Deep Feature Rearrangement
Deep convolutional networks (CNNs) have exhibited their potential in ima...
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Towards Explainable NLP: A Generative Explanation Framework for Text Classification
Building explainable systems is a critical problem in the field of Natur...
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Automatic Design of CNNs via Differentiable Neural Architecture Search for PolSAR Image Classification
Convolutional neural networks (CNNs) have shown good performance in pola...
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Designing and Training of A Dual CNN for Image Denoising
Deep convolutional neural networks (CNNs) for image denoising have recen...
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Attention-over-Attention Neural Networks for Reading Comprehension
Cloze-style queries are representative problems in reading comprehension...
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Particle Filter Re-detection for Visual Tracking via Correlation Filters
Most of the correlation filter based tracking algorithms can achieve goo...
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Hierarchical Siamese Network for Thermal Infrared Object Tracking
Most thermal infrared (TIR) tracking methods are discriminative, which t...
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Integrating Boundary and Center Correlation Filters for Visual Tracking with Aspect Ratio Variation
The aspect ratio variation frequently appears in visual tracking and has...
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Coalition formation for Multi-agent Pursuit based on Neural Network and AGRMF Model
An approach for coalition formation of multi-agent pursuit based on neur...
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Consensus Attention-based Neural Networks for Chinese Reading Comprehension
Reading comprehension has embraced a booming in recent NLP research. Sev...
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Towards well-specified semi-supervised model-based classifiers via structural adaptation
Semi-supervised learning plays an important role in large-scale machine ...
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Automatic Dataset Augmentation
Large scale image dataset and deep convolutional neural network (DCNN) a...
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An End-to-End Compression Framework Based on Convolutional Neural Networks
Deep learning, e.g., convolutional neural networks (CNNs), has achieved ...
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Learning Deep CNN Denoiser Prior for Image Restoration
Model-based optimization methods and discriminative learning methods hav...
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Learning Convolutional Networks for Content-weighted Image Compression
Lossy image compression is generally formulated as a joint rate-distorti...
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Is Second-order Information Helpful for Large-scale Visual Recognition?
By stacking layers of convolution and nonlinearity, convolutional networ...
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Learning a Single Convolutional Super-Resolution Network for Multiple Degradations
Recent years have witnessed the unprecedented success of deep convolutio...
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Saliency Detection via Combining Region-Level and Pixel-Level Predictions with CNNs
This paper proposes a novel saliency detection method by combining regio...
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Random Walk Graph Laplacian based Smoothness Prior for Soft Decoding of JPEG Images
Given the prevalence of JPEG compressed images, optimizing image reconst...
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Feature selection with test cost constraint
Feature selection is an important preprocessing step in machine learning...
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Towards Effective Codebookless Model for Image Classification
The bag-of-features (BoF) model for image classification has been thorou...
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Visualizing and Comparing Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have achieved comparable error rate...
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