Pattern recognition and computer vision Part 11
Efficiently Amalgamated CNN-Transformer Network for Image Super-Resolution Reconstruction.-A hybrid model for video compression based on the fusion of feature compression framework and multi-object tracking network.-Robust Degradation Representation via Efficient Diffusion Model for Blind Super-reso...
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| Weitere Verfasser: | , , , , , , , |
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| Sprache: | eng |
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Singapore
Springer
2024
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| Schriftenreihe: | Lecture notes in computer science
14435 |
| Schlagworte: |
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| Zusammenfassung: | Efficiently Amalgamated CNN-Transformer Network for Image Super-Resolution Reconstruction.-A hybrid model for video compression based on the fusion of feature compression framework and multi-object tracking network.-Robust Degradation Representation via Efficient Diffusion Model for Blind Super-resolution.-MemDNet:Memorizing more exogenous information to dehaze natural hazy image.-Technical Quality-Assisted Image Aesthetics Quality Assessment.-Self-Supervised Low-Light Image Enhancement via Histogram Equalization Prior.-Enhancing GAN Compression by Image Probability Distribution Distillation.-HDTR-Net: A Real-Time High-Definition Teeth Restoration Network for Arbitrary Talking Face Generation Methods.-Multi-stream-based Low-latency Viewport Switching Scheme for Panoramic Videos.-Large Kernel Convolutional Attention based U-Net Network for Inpainting Oracle Bone Inscription.-L^2DM: A Diffusion Model for Low-Light Image Enhancement.-Multi-domain Information Fusion for Key-points Guided GAN Inversion.-Adaptive Low-Light Image Enhancement Optimization Framework with Algorithm Unrolling.-Feature Matching in the Changed Environments for Visual Localization.-To be Critical: Self-Calibrated Weakly Supervised Learning for Salient Object Detection.-Image Visual Complexity Evaluation Based on Deep Ordinal Regression.-Low-light Image Enhancement Based on Mutual Guidance between Enhancing Strength and Image Appearance.-Semantic-Guided Completion Network for Video Inpainting in Complex Urban Scene.-Anime Sketch Coloring Based on Self-Attention Gate and Progressive PatchGAN.-TransDDPM: Transformer-based Denoising Diffusion Probabilistic Model for image Restoration.-One-Stage Wireframe Parsing in Fish-eye Images.-Out-of-Distribution with Text-to-Image Diffusion Models.-Generalized Zero-Shot Learning with Noisy Labeled Data.-Q-TrHDRI: A Qurey-based Transformer for High Dynamic Range Imaging with Dynamic Scenes.-FRNet: Improving Face De-Occlusion via Feature Reconstruction.-Semantically Guided Bi-level Adaptation for Cross Domain Crowd Counting.-Joint Priors-Based Restoration Method for Degraded Images Under Medium Propagation.-GridIIS: Grid based Interactive Image Segmentation.-ADORE: Adaptive Diffusion Optimized Restoration for AI-generated Facial Imagery.-TU-former: A hybrid U-shaped Transformer network for SAR image denoising.-New Insights on the Generation of Rain Streaks: Generating-Removing United Unpaired Image Deraining Network.-Knowledge Transfer via Leveraging Teacher-Student Network with Visual Attention to Enhance Atmospheric Sand Image Restoration.-Enhancing Image-to-Image Translation with Contrast Loss Constrained Generators and Selective Neighborhood Sampling.-Dynamic Neural Networks for Adaptive Implicit Image Compression.-Misalignment Insensitive Perceptual Metric for Full Reference Image Quality Assessment.-A Mutual Enhancement Framework for Specular Highlight Detection and Removal.-Pixel-Level Sonar Image JND Based on Inexact Supervised Learning.-Discriminative Activation of Information is what you need in Image Super-Resolution Transformer.-SentiImgBank: A Large Scale Visual Repository for Image Sentiment Analysis.-MSED: A Robust Ellipse Detector With Multi-Scale Merging and Validation. 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, 521 Seiten Illustrationen, Diagramme |
| ISBN: | 9789819985517 978-981-99-8551-7 |