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Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans
The COVID-19 pandemic has spread globally for several months. Because it...
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RepVGG: Making VGG-style ConvNets Great Again
We present a simple but powerful architecture of convolutional neural ne...
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Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation
Thanks to large-scale labeled training data, deep neural networks (DNNs)...
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Lossless CNN Channel Pruning via Gradient Resetting and Convolutional Re-parameterization
Channel pruning (a.k.a. filter pruning) aims to slim down a convolutiona...
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Shallow Feature Based Dense Attention Network for Crowd Counting
While the performance of crowd counting via deep learning has been impro...
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PANDA: A Gigapixel-level Human-centric Video Dataset
We present PANDA, the first gigaPixel-level humAN-centric viDeo dAtaset,...
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IMRAM: Iterative Matching with Recurrent Attention Memory for Cross-Modal Image-Text Retrieval
Enabling bi-directional retrieval of images and texts is important for u...
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Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification
In real-world scenarios, data tends to exhibit a long-tailed, imbalanced...
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Global Sparse Momentum SGD for Pruning Very Deep Neural Networks
Deep Neural Network (DNN) is powerful but computationally expensive and ...
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PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion Regression
Existing methods on visual emotion analysis mainly focus on coarse-grain...
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ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks
As designing appropriate Convolutional Neural Network (CNN) architecture...
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GRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity Recognition
The dominant approaches for named entity recognition (NER) mostly adopt ...
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Incremental Few-Shot Learning for Pedestrian Attribute Recognition
Pedestrian attribute recognition has received increasing attention due t...
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Adaptive Region Embedding for Text Classification
Deep learning models such as convolutional neural networks and recurrent...
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Approximated Oracle Filter Pruning for Destructive CNN Width Optimization
It is not easy to design and run Convolutional Neural Networks (CNNs) du...
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Centripetal SGD for Pruning Very Deep Convolutional Networks with Complicated Structure
The redundancy is widely recognized in Convolutional Neural Networks (CN...
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From Zero-shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis
Robust object recognition systems usually rely on powerful feature extra...
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