2,915 Result(s)
within
Chapter
**lu Chen
Image Processing and Computer Vision
Pattern Recognition
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Chapter and Conference Paper
Multi-level Patch Transformer for Style Transfer with Single Reference Image
Despite the recent success of image style transfer with Generative Adversarial Networks (GANs), this task remains challenging due to the requirements of large volumes of style image data. In this work, we pres...
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Chapter and Conference Paper
Improving Small License Plate Detection with Bidirectional Vehicle-Plate Relation
License plate detection is a critical component of license plate recognition systems. A challenge in this domain is detecting small license plates captured at a considerable distance. Previous researchers have...
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Chapter and Conference Paper
Adversarially Robust Deepfake Detection via Adversarial Feature Similarity Learning
Deepfake technology has raised concerns about the authenticity of digital content, necessitating the development of effective detection methods. However, the widespread availability of deepfakes has given rise...
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Chapter and Conference Paper
Gait Recognition Based on Temporal Gait Information Enhancing
Gait recognition is a long range biometric technology that identifies individuals by their walking patterns. Currently, gait recognition primarily extracts gait features using convolutional neural networks, wh...
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Chapter and Conference Paper
MARS: An Instance-Aware, Modular and Realistic Simulator for Autonomous Driving
Nowadays, autonomous cars can drive smoothly in ordinary cases, and it is widely recognized that realistic sensor simulation will play a critical role in solving remaining corner cases by simulating them. To t...
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Chapter and Conference Paper
A Purified Stacking Ensemble Framework for Cytology Classification
Cancer is one of the fatal threats to human beings. However, early detection and diagnosis can significantly reduce death risk, in which cytology classification is indispensable. Researchers have proposed many...
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Chapter and Conference Paper
Irregular License Plate Recognition via Global Information Integration
Irregular license plate recognition remains challenging due to the irregular layouts of characters, such as multi-line and perspective-distorted layouts. Many previous methods are based on different attention ...
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Chapter and Conference Paper
TNT-Net: Point Cloud Completion by Transformer in Transformer
Estimating the overall structure of a point cloud from a partial 3D point cloud input is a crucial task in computer vision. However, existing point cloud completion methods often overlook object detail informa...
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Chapter and Conference Paper
Weakly Supervised Optical Remote Sensing Salient Object Detection Based on Adaptive Discriminative Region Suppression
Salient object detection in optical remote sensing images aims to detect attractive objects from optical remote sensing images, providing important prior information for many remote sensing tasks, which have r...
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Chapter and Conference Paper
Fast Hierarchical Depth Super-Resolution via Guided Attention
Depth maps captured by mainstream depth sensors are still of low resolution compared with color images. The main difficulties in depth super-resolution lie in the recovery of tiny textures from severely unders...
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Chapter and Conference Paper
C3-PO: A Convolutional Neural Network for COVID Onset Prediction from Cough Sounds
This study presents a novel approach to diagnosing the highly contagious COVID-19 respiratory disease. Traditional diagnosis methods, such as polymerase chain reaction (PCR) and rapid antigen test (RAT), have ...
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Chapter and Conference Paper
Weakly-Supervised Grounding for VQA with Dual Visual-Linguistic Interaction
Visual question answer (VQA) grounding, aimed at locating the visual evidence associated with the answers while answering questions, has attracted increasing research interest. To locate the evidence, most exi...
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Chapter and Conference Paper
Semantic Transition Detection for Self-supervised Video Scene Segmentation
Video scene segmentation is a crucial task in temporally parsing long-form videos into basic story units. Most advanced self-supervised methods of video scene segmentation focus heavily on learning video shot ...
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Chapter and Conference Paper
Equivariant Indoor Illumination Map Estimation from a Single Image
Thanks to the recent development of inverse rendering, photorealistic re-synthesis of indoor scenes have brought augmented reality closer to reality. All-angle environment illumination map estimation of arbitr...
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Chapter and Conference Paper
Global-to-Local Feature Mining Network for RGB-Infrared Person Re-Identification
RGB-Infrared person Re-Identification (RGB-IR ReID) is a challenging matching task that retrieves a RGB/infrared pedestrian image from the existing infrared/RGB set captured by non-overlap** visible or infra...
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Chapter and Conference Paper
Pseudo-label Based Unsupervised Momentum Representation Learning for Multi-domain Image Retrieval
Although many current cross-domain image retrieval researches have made good progress, most of the works is targeted at specific domains. At the same time, we also noticed that many works are based on manually...
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Chapter and Conference Paper
STU3: Multi-organ CT Medical Image Segmentation Model Based on Transformer and UNet
With the popularity of artificial intelligence applications in the medical field, U-shaped convolutional neural network (CNN) has garnered significant attention for their efficacy in medical image analysis tas...
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Chapter and Conference Paper
Lightweight Image Captioning Model Based on Knowledge Distillation
The performance of image captioning models based on deep learning has been significantly improved compared with traditional algorithms. However, due to the complex network structure and huge parameters, these ...
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Chapter and Conference Paper
AST: An Attention-Guided Segment Transformer for Drone-Based Cross-View Geo-Localization
To tackle the problem of drone-based cross-view geo-localization, we address how to match drone-view images and satellite-view images, which is extremely challenging due to the variability of view angles and v...
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Chapter and Conference Paper
CESegNet:Context-Enhancement Semantic Segmentation Network Based on Transformer
CNN-based methods have achieved success in semantic segmentation. However, research on improving network robustness in this domain has been limited. Similarly, transformer and its variants have recently shown ...
