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Weak NAS Predictors Are All You Need
Neural Architecture Search (NAS) finds the best network architecture by ...
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Meta-PU: An Arbitrary-Scale Upsampling Network for Point Cloud
Point cloud upsampling is vital for the quality of the mesh in three-dim...
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COIN: Contrastive Identifier Network for Breast Mass Diagnosis in Mammography
Computer-aided breast cancer diagnosis in mammography is a challenging p...
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Improved Image Matting via Real-time User Clicks and Uncertainty Estimation
Image matting is a fundamental and challenging problem in computer visio...
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Are Fewer Labels Possible for Few-shot Learning?
Few-shot learning is challenging due to its very limited data and labels...
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Semantic Image Synthesis via Efficient Class-Adaptive Normalization
Spatially-adaptive normalization (SPADE) is remarkably successful recent...
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Identity-Driven DeepFake Detection
DeepFake detection has so far been dominated by “artifact-driven” method...
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Unsupervised Pre-training for Person Re-identification
In this paper, we present a large scale unlabeled person re-identificati...
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MicroNet: Towards Image Recognition with Extremely Low FLOPs
In this paper, we present MicroNet, which is an efficient convolutional ...
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LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud-based Deep Networks
Deep neural networks have made tremendous progress in 3D point-cloud rec...
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MichiGAN: Multi-Input-Conditioned Hair Image Generation for Portrait Editing
Despite the recent success of face image generation with GANs, condition...
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Passport-aware Normalization for Deep Model Protection
Despite tremendous success in many application scenarios, deep learning ...
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GreedyFool: Distortion-Aware Sparse Adversarial Attack
Modern deep neural networks(DNNs) are vulnerable to adversarial samples....
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Improving Person Re-identification with Iterative Impression Aggregation
Our impression about one person often updates after we see more aspects ...
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Old Photo Restoration via Deep Latent Space Translation
We propose to restore old photos that suffer from severe degradation thr...
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Dual Convolutional Neural Networks for Breast Mass Segmentation and Diagnosis in Mammography
Deep convolutional neural networks (CNNs) have emerged as a new paradigm...
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Compressive MR Fingerprinting reconstruction with Neural Proximal Gradient iterations
Consistency of the predictions with respect to the physical forward mode...
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Bringing Old Photos Back to Life
We propose to restore old photos that suffer from severe degradation thr...
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Rethinking Spatially-Adaptive Normalization
Spatially-adaptive normalization is remarkably successful recently in co...
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Density-Aware Graph for Deep Semi-Supervised Visual Recognition
Semi-supervised learning (SSL) has been extensively studied to improve t...
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DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search
Efficient search is a core issue in Neural Architecture Search (NAS). It...
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Dynamic ReLU
Rectified linear units (ReLU) are commonly used in deep neural networks....
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Model Watermarking for Image Processing Networks
Deep learning has achieved tremendous success in numerous industrial app...
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Deep Reflection Prior
Reflections are very common phenomena in our daily photography, which di...
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Dynamic Convolution: Attention over Convolution Kernels
Light-weight convolutional neural networks (CNNs) suffer performance deg...
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Deep Decomposition Learning for Inverse Imaging Problems
Deep learning is emerging as a new paradigm for solving inverse imaging ...
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Once a MAN: Towards Multi-Target Attack via Learning Multi-Target Adversarial Network Once
Modern deep neural networks are often vulnerable to adversarial samples....
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A General Decoupled Learning Framework for Parameterized Image Operators
Many different deep networks have been used to approximate, accelerate o...
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Signed Laplacian Deep Learning with Adversarial Augmentation for Improved Mammography Diagnosis
Computer-aided breast cancer diagnosis in mammography is limited by inad...
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Inferring the Importance of Product Appearance: A Step Towards the Screenless Revolution
Nowadays, almost all the online orders were placed through screened devi...
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A Deep DUAL-PATH Network for Improved Mammogram Image Processing
We present, for the first time, a novel deep neural network architecture...
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Transductive Zero-Shot Learning with Visual Structure Constraint
Zero-shot Learning (ZSL) aims to recognize objects of the unseen classes...
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Gated Context Aggregation Network for Image Dehazing and Deraining
Image dehazing aims to recover the uncorrupted content from a hazy image...
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Emerging Applications of Reversible Data Hiding
Reversible data hiding (RDH) is one special type of information hiding, ...
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A deep learning approach for Magnetic Resonance Fingerprinting
Current popular methods for Magnetic Resonance Fingerprint (MRF) recover...
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Learning Discriminative Representation with Signed Laplacian Restricted Boltzmann Machine
We investigate the potential of a restricted Boltzmann Machine (RBM) for...
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Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-net
We explore the use of deep learning for breast mass segmentation in mamm...
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Decouple Learning for Parameterized Image Operators
Many different deep networks have been used to approximate, accelerate o...
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Deep Exemplar-based Colorization
We propose the first deep learning approach for exemplar-based local col...
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Stereoscopic Neural Style Transfer
This paper presents the first attempt at stereoscopic neural style trans...
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Coherent Online Video Style Transfer
Training a feed-forward network for fast neural style transfer of images...
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StyleBank: An Explicit Representation for Neural Image Style Transfer
We propose StyleBank, which is composed of multiple convolution filter b...
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