Pattern recognition and computer vision Part 6
RSID: A remote sensing image dehazing network.-ContextNet: Learning Context Information for Texture-less Light Field Depth Estimation.-An Efficient Way for Active None-line-of-sight: End-to-end Learned Compressed NLOS Imaging.-DFAR-Net: Dual-Input Three-Branch Attention Fusion Reconstruction Network...
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| Weitere Verfasser: | , , , , , , , |
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| Sprache: | eng |
| Veröffentlicht: |
Singapore
Springer
2024
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| Schriftenreihe: | Lecture notes in computer science
14430 |
| Schlagworte: |
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> COMPUTERS / Artificial Intelligence
> COMPUTERS / Computer Vision & Pattern Recognition
> COMPUTERS / Hardware / Network Hardware
> COMPUTERS / Information Technology
> COMPUTERS / Networking / General
> Computer networking & communications
> Computer vision
> Computerhardware
> Machine learning
> Maschinelles Lernen
> Network hardware
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> Systems analysis & design
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| Zusammenfassung: | RSID: A remote sensing image dehazing network.-ContextNet: Learning Context Information for Texture-less Light Field Depth Estimation.-An Efficient Way for Active None-line-of-sight: End-to-end Learned Compressed NLOS Imaging.-DFAR-Net: Dual-Input Three-Branch Attention Fusion Reconstruction Network for Polarized Non-Line-of-Sight Imaging.-EVCPP:Example-driven Virtual Camera Pose Prediction for cloud performing arts scenes.-RBSR: Efficient and Flexible Recurrent Network for Burst Super-Resolution.-WDU-Net: Wavelet-Guided Deep Unfolding Network for Image Compressed Sensing Reconstruction.-Memory-Augmented Spatial-Temporal Consistency Network for Video Anomaly Detection.-Frequency and Spatial Domain Filter Network for Visual Object Tracking.-Enhancing Feature Representation for Anomaly Detection via Local-and-Global Temporal Relations and a Multi-Stage Memory.-DFAformer: A Dual Filtering Auxiliary Transformer for Efficient Online Action Detection in Streaming Videos.-Relation-guided Multi-stage Feature Aggregation Network for Video Object Detection.-Multimodal Local Feature Enhancement Network for Video Summarization.-Asymmetric Attention Fusion for Unsupervised Video Object Segmentatio.-Flow-Guided Diffusion Autoencoder for Unsupervised Video Anomaly detection.-Prototypical Transformer for Weakly Supervised Action Segmentation.-Unimodal-Multimodal Collaborative Enhancement for Audio-Visual Event Localization.-Dual-memory feature aggregation for video object detection.-Going Beyond Closed Sets: A Multimodal Perspective for Video Emotion Analysis.-Temporal-Semantic Context Fusion for Robust Weakly Supervised Video Anomaly Detection.-A Survey: the Sensor-based Method for Sign Language Recognition.-Utilizing Video Word Boundaries and Feature-based Knowledge Distillation Improving Sentence-level Lip Reading.-Denoised Temporal Relation Network for Temporal Action Segmentation.-3D Lightweight Spatial-Spectral Attention Network for Hyperspectral Image Classification.-Deepfake Detection via Fine-Grained Classification and Global-Local Information Fusion.-Unsupervised Image-to-Image Translation with Style Consistency.-SemanticCrop: Boosting Contrastive Learning via Semantic-cropped Views.-Transformer-based multi-object tracking in unmanned aerial vehicles.-HEI-GAN: A Human-Environment Interaction based GAN for Multimodal Human Trajectory Prediction.-CenterMatch: A Center Matching Method for Semi-supervised Facial Expression Recognition.-Cross-Dataset Distillation with Multi-Tokens for Image Quality Assessment.-Quality-Aware CLIP for Blind Image Quality Assessment.-Multi-Agent Perception via Co-Attentive Communication Mechanism.-DBRNet:Dual-Branch Real-Time Segmentation NetWork For Metal Defect Detection.-MaskDiffuse: Text-guided Face Mask Removal based on Diffusion Models.-Image Generation Based Intra-class Variance Smoothing for Fine-grained Visual Classification.-Cross-Domain Soft Adaptive Teacher for Syn2Real Object Detection.-Dynamic Graph-Driven Heat Diffusion: Enhancing Industrial Semantic Segmentation.-EKGRL: Entity-based Knowledge Graph Representation Learning for Fact-based Visual Question Answering.-Disentangled Attribute Features Vision Transformer for Pedestrian Attribute Recognition.-A high-resolution network based on feature redundancy reduction and attention mechanism. The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13-15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | xiv, 525 Seiten Illustrationen, Diagramme |
| ISBN: | 9789819985364 978-981-99-8536-4 |