
PAMS: Quantized SuperResolution via Parameterized Max Scale
Deep convolutional neural networks (DCNNs) have shown dominant performan...
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Rotated Binary Neural Network
Binary Neural Network (BNN) shows its predominance in reducing the compl...
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The 1st Tiny Object Detection Challenge:Methods and Results
The 1st Tiny Object Detection (TOD) Challenge aims toencourage research ...
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Binarized Neural Architecture Search for Efficient Object Recognition
Traditional neural architecture search (NAS) has a significant impact in...
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AntiBandit Neural Architecture Search for Model Defense
Deep convolutional neural networks (DCNNs) have dominated as the best pe...
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iffDetector: Inferenceaware Feature Filtering for Object Detection
Modern CNNbased object detectors focus on feature configuration during ...
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Cogradient Descent for Bilinear Optimization
Conventional learning methods simplify the bilinear model by regarding t...
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NASCount: CountingbyDensity with Neural Architecture Search
Most of the recent advances in crowd counting have evolved from handdes...
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HRank: Filter Pruning using HighRank Feature Map
Neural network pruning offers a promising prospect to facilitate deployi...
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Channel Pruning via Automatic Structure Search
Channel pruning is among the predominant approaches to compress deep neu...
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Binarized Neural Architecture Search
Neural architecture search (NAS) can have a significant impact in comput...
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GBCNs: Genetic Binary Convolutional Networks for Enhancing the Performance of 1bit DCNNs
Training 1bit deep convolutional neural networks (DCNNs) is one of the ...
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Aggregation Signature for Small Object Tracking
Small object tracking becomes an increasingly important task, which howe...
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Circulant Binary Convolutional Networks: Enhancing the Performance of 1bit DCNNs with Circulant Back Propagation
The rapidly decreasing computation and memory cost has recently driven t...
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Semanticaware Image Deblurring
Image deblurring has achieved exciting progress in recent years. However...
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RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1bit DCNNs
Binarized convolutional neural networks (BCNNs) are widely used to impro...
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Bayesian Optimized 1Bit CNNs
Deep convolutional neural networks (DCNNs) have dominated the recent dev...
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Dynamic Neural Network Decoupling
Convolutional neural networks (CNNs) have achieved a superior performanc...
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Supervised Online Hashing via Similarity Distribution Learning
Online hashing has attracted extensive research attention when facing st...
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Dynamic Distribution Pruning for Efficient Network Architecture Search
Network architectures obtained by Neural Architecture Search (NAS) have ...
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Multinomial Distribution Learning for Effective Neural Architecture Search
Architectures obtained by Neural Architecture Search (NAS) have achieved...
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Towards Optimal Structured CNN Pruning via Generative Adversarial Learning
Structured pruning of filters or neurons has received increased focus fo...
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Crowd Counting and Density Estimation by Trellis EncoderDecoder Network
Crowd counting has recently attracted increasing interest in computer vi...
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Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression
Compressing convolutional neural networks (CNNs) has received everincre...
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Projection Convolutional Neural Networks for 1bit CNNs via Discrete Back Propagation
The advancement of deep convolutional neural networks (DCNNs) has driven...
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Object detection and tracking benchmark in industry based on improved correlation filter
Realtime object detection and tracking have shown to be the basis of in...
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Memory Attention Networks for Skeletonbased Action Recognition
Skeletonbased action recognition task is entangled with complex spatio...
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OneTwoOne Networks for Compression Artifacts Reduction in Remote Sensing
Compression artifacts reduction (CAR) is a challenging problem in the fi...
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The Structure Transfer Machine Theory and Applications
Representation learning is a fundamental but challenging problem, especi...
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Latent Constrained Correlation Filter
Correlation filters are special classifiers designed for shiftinvariant...
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Manifold Constrained LowRank Decomposition
Lowrank decomposition (LRD) is a stateoftheart method for visual dat...
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Deep Fisher Discriminant Learning for Mobile Hand Gesture Recognition
Gesture recognition is a challenging problem in the field of biometrics....
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Deep Spatiotemporal Manifold Network for Action Recognition
Visual data such as videos are often sampled from complex manifold. We p...
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Gabor Convolutional Networks
Steerable properties dominate the design of traditional filters, e.g., G...
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Output Constraint Transfer for Kernelized Correlation Filter in Tracking
Kernelized Correlation Filter (KCF) is one of the stateoftheart objec...
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Selflearning Scenespecific Pedestrian Detectors using a Progressive Latent Model
In this paper, a selflearning approach is proposed towards solving scen...
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Latent Constrained Correlation Filters for Object Localization
There is a neglected fact in the traditional machine learning methods th...
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Boostinglike Deep Learning For Pedestrian Detection
This paper proposes boostinglike deep learning (BDL) framework for pede...
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