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Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks
Deep neural networks often consist of a great number of trainable parame...
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AttentionGAN: Unpaired Image-to-Image Translation using Attention-Guided Generative Adversarial Networks
State-of-the-art methods in the unpaired image-to-image translation are ...
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Influenza Modeling Based on Massive Feature Engineering and International Flow Deconvolution
In this article, we focus on the analysis of the potential factors drivi...
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On the Anomalous Generalization of GANs
Generative models, especially Generative Adversarial Networks (GANs), ha...
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Relationship-Aware Spatial Perception Fusion for Realistic Scene Layout Generation
The significant progress on Generative Adversarial Networks (GANs) have ...
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Spatial-Scale Aligned Network for Fine-Grained Recognition
Existing approaches for fine-grained visual recognition focus on learnin...
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When Dictionary Learning Meets Deep Learning: Deep Dictionary Learning and Coding Network for Image Recognition with Limited Data
We present a new Deep Dictionary Learning and Coding Network (DDLCN) for...
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ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context
Predicting the patient's clinical outcome from the historical electronic...
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Unified Generative Adversarial Networks for Controllable Image-to-Image Translation
Controllable image-to-image translation, i.e., transferring an image fro...
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AdderNet: Do We Really Need Multiplications in Deep Learning?
Compared with cheap addition operation, multiplication operation is of m...
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Non-local Recurrent Neural Memory for Supervised Sequence Modeling
Typical methods for supervised sequence modeling are built upon the recu...
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Exploring Frequency Domain Interpretation of Convolutional Neural Networks
Many existing interpretation methods of convolutional neural networks (C...
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Learning Depth-Guided Convolutions for Monocular 3D Object Detection
3D object detection from a single image without LiDAR is a challenging t...
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Asymmetric Generative Adversarial Networks for Image-to-Image Translation
State-of-the-art models for unpaired image-to-image translation with Gen...
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Differentiable Feature Aggregation Search for Knowledge Distillation
Knowledge distillation has become increasingly important in model compre...
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Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry
We propose a self-supervised learning framework for visual odometry (VO)...
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Graph-Based Parallel Large Scale Structure from Motion
While Structure from Motion (SfM) achieves great success in 3D reconstru...
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Generative 3D Part Assembly via Dynamic Graph Learning
Autonomous part assembly is a challenging yet crucial task in 3D compute...
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Multi-mapping Image-to-Image Translation via Learning Disentanglement
Recent advances of image-to-image translation focus on learning the one-...
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GhostNet: More Features from Cheap Operations
Deploying convolutional neural networks (CNNs) on embedded devices is di...
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Implicit Normalizing Flows
Normalizing flows define a probability distribution by an explicit inver...
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MetaFuse: A Pre-trained Fusion Model for Human Pose Estimation
Cross view feature fusion is the key to address the occlusion problem in...
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Large Margin Multi-modal Multi-task Feature Extraction for Image Classification
The features used in many image analysis-based applications are frequent...
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GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
Molecular graph generation is a fundamental problem for drug discovery a...
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Boundary Content Graph Neural Network for Temporal Action Proposal Generation
Temporal action proposal generation plays an important role in video act...
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Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field
Surgical skill assessment is important for surgery training and quality ...
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Incorporating Human Domain Knowledge in 3D LiDAR-based Semantic Segmentation
This work studies semantic segmentation using 3D LiDAR data. Popular dee...
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Defective Convolutional Layers Learn Robust CNNs
Robustness of convolutional neural networks has recently been highlighte...
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Single Image Deraining: From Model-Based to Data-Driven and Beyond
Rain removal or deraining methods attempt to restore the clean backgroun...
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TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting
We present a lightweight video motion retargeting approach TransMoMo tha...
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RANDOM MASK: Towards Robust Convolutional Neural Networks
Robustness of neural networks has recently been highlighted by the adver...
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Image Smoothing via Unsupervised Learning
Image smoothing represents a fundamental component of many disparate com...
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Stroke-based Artistic Rendering Agent with Deep Reinforcement Learning
Excellent painters can use only a few strokes to create a fantastic pain...
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TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding
We aim at solving the problem of predicting people's ideology, or politi...
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TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning
Fusing data from multiple modalities provides more information to train ...
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Reasoning Over Semantic-Level Graph for Fact Checking
We study fact-checking in this paper, which aims to verify a textual cla...
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Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View
Graph Neural Networks (GNNs) have achieved promising performance on a wi...
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Joint Learning of Graph Representation and Node Features in Graph Convolutional Neural Networks
Graph Convolutional Neural Networks (GCNNs) extend classical CNNs to gra...
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CARS: Continuous Evolution for Efficient Neural Architecture Search
Searching techniques in most of existing neural architecture search (NAS...
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Mathematical Analysis of Adversarial Attacks
In this paper, we analyze efficacy of the fast gradient sign method (FGS...
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Exploring Hypergraph Representation on Face Anti-spoofing Beyond 2D Attacks
Face anti-spoofing plays a crucial role in protecting face recognition s...
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L_DMI: An Information-theoretic Noise-robust Loss Function
Accurately annotating large scale dataset is notoriously expensive both ...
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Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks
In the future 6th generation networks, ultra-reliable and low-latency co...
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Improve bone age assessment by learning from anatomical local regions
Skeletal bone age assessment (BAA), as an essential imaging examination,...
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FFA-Net: Feature Fusion Attention Network for Single Image Dehazing
In this paper, we propose an end-to-end feature fusion at-tention networ...
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Recurrent Exposure Generation for Low-Light Face Detection
Face detection from low-light images is challenging due to limited photo...
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Learning Robust Representation for Clustering through Locality Preserving Variational Discriminative Network
Clustering is one of the fundamental problems in unsupervised learning. ...
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Learnable Embedding Space for Efficient Neural Architecture Compression
We propose a method to incrementally learn an embedding space over the d...
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Exploring Reciprocal Attention for Salient Object Detection by Cooperative Learning
Typically, objects with the same semantics are not always prominent in i...
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NASNet: A Neuron Attention Stage-by-Stage Net for Single Image Deraining
Images captured under complicated rain conditions often suffer from noti...
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