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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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Weight-Sharing Neural Architecture Search: A Battle to Shrink the Optimization Gap
Neural architecture search (NAS) has attracted increasing attentions in ...
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AdderNet and its Minimalist Hardware Design for Energy-Efficient Artificial Intelligence
Convolutional neural networks (CNN) have been widely used for boosting t...
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Appending Adversarial Frames for Universal Video Attack
There have been many efforts in attacking image classification models wi...
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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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Revisit Knowledge Distillation: a Teacher-free Framework
Knowledge Distillation (KD) aims to distill the knowledge of a cumbersom...
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Towards a practical measure of interference for reinforcement learning
Catastrophic interference is common in many network-based learning syste...
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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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Few-shot Adaptive Faster R-CNN
To mitigate the detection performance drop caused by domain shift, we ai...
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Is Fast Adaptation All You Need?
Gradient-based meta-learning has proven to be highly effective at learni...
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RefinedMPL: Refined Monocular PseudoLiDAR for 3D Object Detection in Autonomous Driving
In this paper, we strive for solving the ambiguities arisen by the astou...
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GhostNet: More Features from Cheap Operations
Deploying convolutional neural networks (CNNs) on embedded devices is di...
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AdvHat: Real-world adversarial attack on ArcFace Face ID system
In this paper we propose a novel easily reproducible technique to attack...
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Less Is Better: Unweighted Data Subsampling via Influence Function
In the time of Big Data, training complex models on large-scale data set...
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Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors
The impressive performance of deep convolutional neural networks in sing...
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Generate High-Resolution Adversarial Samples by Identifying Effective Features
As the prevalence of deep learning in computer vision, adversarial sampl...
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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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Deep Multimodal Neural Architecture Search
Designing effective neural networks is fundamentally important in deep m...
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Real-world attack on MTCNN face detection system
Recent studies proved that deep learning approaches achieve remarkable r...
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Scalable NAS with Factorizable Architectural Parameters
Neural architecture search (NAS) is an emerging topic in machine learnin...
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Pose Agnostic Cross-spectral Hallucination via Disentangling Independent Factors
The cross-sensor gap is one of the challenges that arise much research i...
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Optimally Combining Classifiers for Semi-Supervised Learning
This paper considers semi-supervised learning for tabular data. It is wi...
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AI Benchmark: Running Deep Neural Networks on Android Smartphones
Over the last years, the computational power of mobile devices such as s...
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SteReFo: Efficient Image Refocusing with Stereo Vision
Whether to attract viewer attention to a particular object, give the imp...
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Learning beyond Predefined Label Space via Bayesian Nonparametric Topic Modelling
In real world machine learning applications, testing data may contain so...
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Coordinates-based Resource Allocation Through Supervised Machine Learning
Appropriate allocation of system resources is essential for meeting the ...
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Distilling portable Generative Adversarial Networks for Image Translation
Despite Generative Adversarial Networks (GANs) have been widely used in ...
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Explore Training of Deep Convolutional Neural Networks on Battery-powered Mobile Devices: Design and Application
The fast-growing smart applications on mobile devices leverage pre-train...
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PPD: Permutation Phase Defense Against Adversarial Examples in Deep Learning
Deep neural networks have demonstrated cutting edge performance on vario...
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Discernible Compressed Images via Deep Perception Consistency
Image compression, as one of the fundamental low-level image processing ...
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HourNAS: Extremely Fast Neural Architecture Search Through an Hourglass Lens
Neural Architecture Search (NAS) refers to automatically design the arch...
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DeepMnemonic: Password Mnemonic Generation via Deep Attentive Encoder-Decoder Model
Strong passwords are fundamental to the security of password-based user ...
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Bidirectional Attention Network for Monocular Depth Estimation
In this paper, we propose a Bidirectional Attention Network (BANet), an ...
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Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning
Social psychology and real experiences show that cognitive consistency p...
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Adversarial AutoAugment
Data augmentation (DA) has been widely utilized to improve generalizatio...
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Image Generation from Freehand Scene Sketches
We introduce the first method for automatic image generation from scene-...
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DeepMark++: CenterNet-based Clothing Detection
The single-stage approach for fast clothing detection as a modification ...
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Data-Free Learning of Student Networks
Learning portable neural networks is very essential for computer vision ...
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RNAS: Architecture Ranking for Powerful Networks
Neural Architecture Search (NAS) is attractive for automatically produci...
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Super Resolution Using Segmentation-Prior Self-Attention Generative Adversarial Network
Convolutional Neural Network (CNN) is intensively implemented to solve s...
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Multimodal Unified Attention Networks for Vision-and-Language Interactions
Learning an effective attention mechanism for multimodal data is importa...
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Perception as prediction using general value functions in autonomous driving applications
We propose and demonstrate a framework called perception as prediction f...
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Triple-GAIL: A Multi-Modal Imitation Learning Framework with Generative Adversarial Nets
Generative adversarial imitation learning (GAIL) has shown promising res...
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Adversarial Domain Adaptation with Domain Mixup
Recent works on domain adaptation reveal the effectiveness of adversaria...
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TensorOpt: Exploring the Tradeoffs in Distributed DNN Training with Auto-Parallelism
A good parallelization strategy can significantly improve the efficiency...
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GOLD-NAS: Gradual, One-Level, Differentiable
There has been a large literature of neural architecture search, but mos...
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Positive-Unlabeled Compression on the Cloud
Many attempts have been done to extend the great success of convolutiona...
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FastLR: Non-Autoregressive Lipreading Model with Integrate-and-Fire
Lipreading is an impressive technique and there has been a definite impr...
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Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network
Most state of the art deep neural networks are overparameterized and exh...
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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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