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Capsule Network is Not More Robust than Convolutional Network
The Capsule Network is widely believed to be more robust than Convolutio...
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Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
This paper presents a new vision Transformer, called Swin Transformer, t...
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Boosting Adversarial Transferability through Enhanced Momentum
Deep learning models are known to be vulnerable to adversarial examples ...
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Energy-Efficient Task Offloading and Resource Allocation for Multiple Access Mobile Edge Computing
In this paper, the problem of joint radio and computation resource manag...
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Energy-efficient Task Offloading for Relay Aided Mobile Edge Computing under Sequential Task Dependency
In this paper, we study a mobile edge computing (MEC) system in which th...
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Robustness of on-device Models: Adversarial Attack to Deep Learning Models on Android Apps
Deep learning has shown its power in many applications, including object...
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Global Context Networks
The Non-Local Network (NLNet) presents a pioneering approach for capturi...
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Depth-Enhanced Feature Pyramid Network for Occlusion-Aware Verification of Buildings from Oblique Images
Detecting the changes of buildings in urban environments is essential. E...
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Energy-Efficient Task Offloading and Resource Allocation in Mobile Edge Computing with Sequential Task Dependency
In this paper, we investigate the computation task with its sub-tasks su...
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Structure-Aware Completion of Photogrammetric Meshes in Urban Road Environment
Photogrammetric mesh models obtained from aerial oblique images have bee...
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Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning
Contrastive learning methods for unsupervised visual representation lear...
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RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder
Existing object detection frameworks are usually built on a single forma...
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RepPoints V2: Verification Meets Regression for Object Detection
Verification and regression are two general methodologies for prediction...
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Parametric Instance Classification for Unsupervised Visual Feature Learning
This paper presents parametric instance classification (PIC) for unsuper...
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Disentangled Non-Local Neural Networks
The non-local block is a popular module for strengthening the context mo...
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Ontology-based Interpretable Machine Learning for Textual Data
In this paper, we introduce a novel interpreting framework that learns a...
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Memory Enhanced Global-Local Aggregation for Video Object Detection
How do humans recognize an object in a piece of video? Due to the deteri...
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Negative Margin Matters: Understanding Margin in Few-shot Classification
This paper introduces a negative margin loss to metric learning based fe...
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Leveraging Photogrammetric Mesh Models for Aerial-Ground Feature Point Matching Toward Integrated 3D Reconstruction
Integration of aerial and ground images has been proved as an efficient ...
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Fast and Regularized Reconstruction of Building Façades from Street-View Images using Binary Integer Programming
Regularized arrangement of primitives on building façades to aligned loc...
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Deep Fusion of Local and Non-Local Features for Precision Landslide Recognition
Precision mapping of landslide inventory is crucial for hazard mitigatio...
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DeepRS: Deep-learning Based Network-Adaptive FEC for Real-Time Video Communications
This work proposes an innovative approach to handle packet loss in real-...
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Dense RepPoints: Representing Visual Objects with Dense Point Sets
We present an object representation, called Dense RepPoints, for flexibl...
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MAP-Net: Multi Attending Path Neural Network for Building Footprint Extraction from Remote Sensed Imagery
Accurately and efficiently extracting building footprints from a wide ra...
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XCMRC: Evaluating Cross-lingual Machine Reading Comprehension
We present XCMRC, the first public cross-lingual language understanding ...
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GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
The Non-Local Network (NLNet) presents a pioneering approach for capturi...
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Local Relation Networks for Image Recognition
The convolution layer has been the dominant feature extractor in compute...
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RepPoints: Point Set Representation for Object Detection
Modern object detectors rely heavily on rectangular bounding boxes, such...
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Spatial-Temporal Relation Networks for Multi-Object Tracking
Recent progress in multiple object tracking (MOT) has shown that a robus...
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Preserving Differential Privacy in Adversarial Learning with Provable Robustness
In this paper, we aim to develop a novel mechanism to preserve different...
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Deep Metric Transfer for Label Propagation with Limited Annotated Data
We study object recognition under the constraint that each object class ...
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Deformable ConvNets v2: More Deformable, Better Results
The superior performance of Deformable Convolutional Networks arises fro...
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DeepQoE: A unified Framework for Learning to Predict Video QoE
Motivated by the prowess of deep learning (DL) based techniques in predi...
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Learning Region Features for Object Detection
While most steps in the modern object detection methods are learnable, t...
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Relation Networks for Object Detection
Although it is well believed for years that modeling relations between o...
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Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning
In this paper, we focus on developing a novel mechanism to preserve diff...
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WordSup: Exploiting Word Annotations for Character based Text Detection
Imagery texts are usually organized as a hierarchy of several visual ele...
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Deformable Convolutional Networks
Convolutional neural networks (CNNs) are inherently limited to model geo...
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Power Data Classification: A Hybrid of a Novel Local Time Warping and LSTM
In this paper, for the purpose of data centre energy consumption monitor...
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