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Biblioteca

MARC Lista (tabellare)
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 – September 1, 2023, Proceedings, Part III / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 – September 1, 2023, Proceedings, Part III / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Autore Sheng Bin
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (522 pages)
Disciplina 005.3
Altri autori (Persone) BiLei
KimJinman
Magnenat-ThalmannNadia
ThalmannDaniel
Collana Lecture Notes in Computer Science
Soggetto topico Application software
Computer systems
Computer networks
Data structures (Computer science)
Information theory
Coding theory
Computer science
Computer and Information Systems Applications
Computer System Implementation
Computer Communication Networks
Data Structures and Information Theory
Coding and Information Theory
Theory of Computation
ISBN 3-031-50075-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Detection and Recognition -- Image Analysis and Processing; Image Restoration and Enhancement; Image Attention and Perception -- Reconstruction; Rendering and Animation -- Synthesis and Generation -- Visual Analytics and Modeling; Graphics and AR/VR -- Medical Imaging and Robotics -- Theoretical Analysis; Image Analysis and Visualization in Advanced Medical Imaging Technology -- Empowering Novel Geometric Algebra for Graphics and Engineering.
Record Nr. UNINA-9910805582603321
Sheng Bin  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 – September 1, 2023, Proceedings, Part I / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 – September 1, 2023, Proceedings, Part I / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Autore Sheng Bin
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (509 pages)
Disciplina 005.3
Altri autori (Persone) BiLei
KimJinman
Magnenat-ThalmannNadia
ThalmannDaniel
Collana Lecture Notes in Computer Science
Soggetto topico Application software
Computer systems
Computer networks
Data structures (Computer science)
Information theory
Coding theory
Computer science
Computer and Information Systems Applications
Computer System Implementation
Computer Communication Networks
Data Structures and Information Theory
Coding and Information Theory
Theory of Computation
ISBN 3-031-50069-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Detection and Recognition -- Image Analysis and Processing; Image Restoration and Enhancement; Image Attention and Perception -- Reconstruction; Rendering and Animation -- Synthesis and Generation -- Visual Analytics and Modeling; Graphics and AR/VR -- Medical Imaging and Robotics -- Theoretical Analysis; Image Analysis and Visualization in Advanced Medical Imaging Technology -- Empowering Novel Geometric Algebra for Graphics and Engineering.
Record Nr. UNINA-9910805575303321
Sheng Bin  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28–September 1, 2023, Proceedings, Part II / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28–September 1, 2023, Proceedings, Part II / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (XII, 513 p. 269 illus., 257 illus. in color.)
Disciplina 005.3
Collana Lecture Notes in Computer Science
Soggetto topico Application software
Computer systems
Computer networks
Data structures (Computer science)
Information theory
Coding theory
Computer science
Computer and Information Systems Applications
Computer System Implementation
Computer Communication Networks
Data Structures and Information Theory
Coding and Information Theory
Theory of Computation
ISBN 3-031-50072-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Detection and Recognition -- Image Analysis and Processing; Image Restoration and Enhancement; Image Attention and Perception -- Reconstruction; Rendering and Animation -- Synthesis and Generation -- Visual Analytics and Modeling; Graphics and AR/VR -- Medical Imaging and Robotics -- Theoretical Analysis; Image Analysis and Visualization in Advanced Medical Imaging Technology -- Empowering Novel Geometric Algebra for Graphics and Engineering.
Record Nr. UNINA-9910799215003321
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 – September 1, 2023, Proceedings, Part IV / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 – September 1, 2023, Proceedings, Part IV / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (XII, 404 p. 122 illus., 100 illus. in color.)
Disciplina 005.3
Collana Lecture Notes in Computer Science
Soggetto topico Application software
Computer systems
Computer networks
Data structures (Computer science)
Information theory
Coding theory
Computer science
Computer and Information Systems Applications
Computer System Implementation
Computer Communication Networks
Data Structures and Information Theory
Coding and Information Theory
Theory of Computation
ISBN 3-031-50078-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Detection and Recognition -- Image Analysis and Processing; Image Restoration and Enhancement; Image Attention and Perception -- Reconstruction; Rendering and Animation -- Synthesis and Generation -- Visual Analytics and Modeling; Graphics and AR/VR -- Medical Imaging and Robotics -- Theoretical Analysis; Image Analysis and Visualization in Advanced Medical Imaging Technology -- Empowering Novel Geometric Algebra for Graphics and Engineering.
Record Nr. UNINA-9910799221903321
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28–September 1, 2023, Proceedings, Part II / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28–September 1, 2023, Proceedings, Part II / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (XII, 513 p. 269 illus., 257 illus. in color.)
Disciplina 005.3
Collana Lecture Notes in Computer Science
Soggetto topico Application software
Computer systems
Computer networks
Data structures (Computer science)
Information theory
Coding theory
Computer science
Computer and Information Systems Applications
Computer System Implementation
Computer Communication Networks
Data Structures and Information Theory
Coding and Information Theory
Theory of Computation
ISBN 3-031-50072-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Detection and Recognition -- Image Analysis and Processing; Image Restoration and Enhancement; Image Attention and Perception -- Reconstruction; Rendering and Animation -- Synthesis and Generation -- Visual Analytics and Modeling; Graphics and AR/VR -- Medical Imaging and Robotics -- Theoretical Analysis; Image Analysis and Visualization in Advanced Medical Imaging Technology -- Empowering Novel Geometric Algebra for Graphics and Engineering.
Record Nr. UNISA-996587866203316
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 – September 1, 2023, Proceedings, Part IV / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Advances in Computer Graphics [[electronic resource] ] : 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 – September 1, 2023, Proceedings, Part IV / / edited by Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (XII, 404 p. 122 illus., 100 illus. in color.)
Disciplina 005.3
Collana Lecture Notes in Computer Science
Soggetto topico Application software
Computer systems
Computer networks
Data structures (Computer science)
Information theory
Coding theory
Computer science
Computer and Information Systems Applications
Computer System Implementation
Computer Communication Networks
Data Structures and Information Theory
Coding and Information Theory
Theory of Computation
ISBN 3-031-50078-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Detection and Recognition -- Image Analysis and Processing; Image Restoration and Enhancement; Image Attention and Perception -- Reconstruction; Rendering and Animation -- Synthesis and Generation -- Visual Analytics and Modeling; Graphics and AR/VR -- Medical Imaging and Robotics -- Theoretical Analysis; Image Analysis and Visualization in Advanced Medical Imaging Technology -- Empowering Novel Geometric Algebra for Graphics and Engineering.
Record Nr. UNISA-996587866403316
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in computer graphics : 39th computer graphics international conference, CGI 2022, virtual event, September 12-16, 2022, proceedings / / Nadia Magnenat-Thalmann [and six others], editors
Advances in computer graphics : 39th computer graphics international conference, CGI 2022, virtual event, September 12-16, 2022, proceedings / / Nadia Magnenat-Thalmann [and six others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (590 pages)
Disciplina 006.6869
Collana Lecture notes in computer science
Soggetto topico Computer graphics
ISBN 3-031-23473-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Image Analysis and Processing -- Multi-granularity Feature Attention Fusion Network for Image-Text Sentiment Analysis -- 1 Introduction -- 2 Related Work -- 2.1 Text Sentiment Analysis -- 2.2 Image Sentiment Analysis -- 2.3 Multimodal Sentiment Analysis -- 3 Our Proposed Model -- 3.1 Model Overview -- 3.2 Feature Learning Layer -- 3.3 Interactive Information Fusion Layer -- 3.4 Interactive Information Fusion Layer -- 4 Experimental Results -- 4.1 Dataset Description -- 4.2 Baselines -- 4.3 Experimental Results and Analysis -- 5 Conclusions -- References -- Toward Efficient Image Denoising: A Lightweight Network with Retargeting Supervision Driven Knowledge Distillation*-12pt -- 1 Introduction -- 2 Proposed Method -- 2.1 Lightweight U-shaped Denoising Network: LUNet -- 2.2 Retargeting Supervision Driven Knowledge Distillation -- 3 Experimental Results -- 3.1 Experimental Settings -- 3.2 Quantitative and Qualitative Results -- 3.3 Ablation Studies -- 4 Conclusions -- References -- A Pig Pose Estimation Model for Measuring Pig's Body Size -- 1 Introduction -- 2 Related Work -- 2.1 Measuring Animal Body Size -- 2.2 Key Point Identification -- 2.3 Attention Mechanism -- 3 Our Approach -- 3.1 Our Network Header -- 3.2 Down-Sampling Module -- 3.3 Selection of Key Points -- 4 Experiments -- 4.1 Dataset -- 4.2 Results on Image and Video -- 4.3 Results on Combining Attention Mechanism -- 4.4 Results on Using Our Network Header -- 5 Conclusion -- References -- Topology-Aware Learning for Semi-supervised Cross-domain Retinal Artery/Vein Classification*-12pt -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Spatial Transformation Module -- 2.3 Regional Mixing Module -- 2.4 Loss Function -- 3 Experimental Results -- 3.1 Datasets -- 3.2 Implementation Details -- 3.3 Artery/Vein Classification Performance.
4 Conclusion -- References -- Face Super-Resolution with Better Semantics and More Efficient Guidance -- 1 Introduction -- 2 Method -- 2.1 Overview of the Proposed Framework -- 2.2 Better Semantic Prior -- 2.3 More Efficient Guidance -- 2.4 Loss Functions -- 3 Experiments -- 3.1 Implementation Details -- 3.2 Comparisons with the State-of-the-Arts -- 3.3 Ablation Study -- 4 Conclusion -- References -- Graphs and Networks -- Layout and Display of Network Graphs on a Sphere*-12pt -- 1 Introduction -- 2 Related Work -- 3 Visualization Pipeline -- 4 Graph Visualization Algorithms -- 4.1 Layout - Adaptation of Fruchterman-Reingold Algorithm -- 4.2 Quantitative Evaluation -- 4.3 Visualizing Spheres in Paraview -- 4.4 Mathematical Basis for Visualizing Arcs in Paraview -- 5 Browser-Based Visualization -- 6 Conclusion -- References -- Joint Matrix Factorization and Structure Preserving for Domain Adaptation*-12pt -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Notations -- 3.2 Problem Formulation -- 3.3 Optimization -- 4 Experiments -- 4.1 Datasets Description -- 4.2 Results -- 4.3 Parameter Sensitivity and Ablation Study -- 5 Conclusion -- References -- Graph Adversarial Network with Bottleneck Adapter Tuning for Sign Language Production*-12pt -- 1 Introduction -- 2 Related Work -- 2.1 Sign Language Production -- 2.2 Transfer Learning -- 2.3 Graph Convolutional Network -- 3 Method -- 3.1 Adapter-Based Contextual Representation -- 3.2 Channel-Wise Target Length Predictor -- 3.3 Cross-modal Sign Pose Generator -- 3.4 Spatial-Temporal Graph Convolutional Discriminator -- 3.5 Loss Function -- 4 Experiments -- 4.1 Datasets -- 4.2 Training Settings -- 4.3 Evaluation Metrics -- 4.4 Quantitative Evaluation -- 4.5 Visual Comparison -- 4.6 Ablation Study -- 5 Conclusion -- References -- Estimation and Feature Matching.
Facial Landmarks Based Region-Level Data Augmentation for Gaze Estimation*-12pt -- 1 Introduction -- 2 Related Works -- 2.1 Gaze Estimation -- 2.2 Data Augmentation -- 3 Proposed Method -- 3.1 Facial Landmarks Based Region Mask -- 3.2 Non-eye Regions Data Augmentation -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Performance Comparison -- 4.3 Ablation Studies -- 5 Conclusions -- References -- An Efficient Dense Depth Map Estimation Algorithm Using Direct Stereo Matching for Ultra-Wide-Angle Images*-12pt -- 1 Introduction -- 2 Patch Matching Stereo -- 2.1 Camera Projection Model -- 2.2 Patch Matching Stereo for Ultra-Wide-Angle Images -- 3 Experimental Results -- 3.1 The TUM VI Benchmark -- 3.2 Comparisons -- 3.3 The Oxford RobotCar Dataset -- 4 Conclusion -- References -- Ad-RMS: Adaptive Regional Motion Statistics for Feature Matching Filtering -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Adaptive Regional Division -- 3.2 Regional Motion Statistics -- 4 Experiment -- 4.1 Evaluation -- 4.2 Dataset and Input Data -- 4.3 Parameters -- 4.4 Comparative Analysis of Results -- 5 Summary -- References -- 3D Reconstruction -- Visual Indoor Navigation Using Mobile Augmented Reality -- 1 Introduction -- 2 Related Work -- 2.1 Indoor Navigation System -- 2.2 Positioning and Navigation Technology -- 3 Research Content and Methodology -- 3.1 Plane and Point Cloud Detection and Visualization -- 3.2 Indoor Map Construction -- 3.3 Map Download and Self-positioning -- 3.4 Path Planning and Display -- 4 Experiment -- 5 Analysis of Results -- References -- Cost Volume Pyramid Network with Multi-strategies Range Searching for Multi-view Stereo -- 1 Introduction -- 2 Related Work -- 2.1 Coarse-to-Fine MVS Methods -- 2.2 Depth Sampling Range -- 2.3 Cost Volume -- 3 Methods -- 3.1 Overview -- 3.2 Depth Sampling Range Estimation -- 3.3 Supervise on Cost Volume.
3.4 Loss Function -- 4 Experiment -- 4.1 Dataset -- 4.2 Implementation Details -- 4.3 Results on DTU Dataset -- 4.4 Results on BlendedMVS -- 4.5 Effectiveness of Multi-strategies -- 4.6 Ablation Study -- 5 Conclusion -- References -- Reconstructing the Surface Mesh Representation for Single Neuron -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Branch Identification -- 3.2 Surface Reconstruction of Neurites -- 3.3 Surface Reconstruction of the Soma -- 4 Experiments and Results -- 5 Conclusion -- References -- WEmap: Weakness-Enhancement Mapping for 3D Reconstruction with Sparse Image Sequences -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Initial Reconstruction -- 3.2 Generation of the Enhanced Set -- 3.3 Reconstruction with Weighted Samples -- 4 Experiments -- 4.1 Datasets -- 4.2 Experiments on the Sparse DTU Dataset -- 4.3 Experiments on the Sparse Tanks and Temples Dataset -- 5 Conclusion -- References -- Rendering and Animation -- Comparing Traditional Rendering Techniques to Deep Learning Based Super-Resolution in Fire and Smoke Animations -- 1 Introduction -- 2 Related Work -- 3 TecoGAN -- 3.1 Network Architecture for Video Super-Resolution -- 3.2 Usage -- 4 Dataset Generation -- 4.1 Creating a Smoke Simulation -- 4.2 Multiple Simulations -- 5 Evaluation -- 5.1 Creating Different Renders -- 5.2 Comparing Video Quality -- 5.3 Cross Simulation Comparison -- 6 Conclusion -- References -- Real-Time Light Field Path Tracing -- 1 Introduction -- 2 Related Work -- 3 General Pipeline and Our Implementation -- 3.1 General Pipeline -- 3.2 Our Implementation -- 4 Experiments -- 5 Results -- 5.1 Runtime -- 5.2 Quality -- 6 Conclusions -- References -- Crowd Simulation with Detailed Body Motion and Interaction -- 1 Introduction -- 2 Related Work -- 2.1 Crowd Simulation -- 2.2 Motion Matching -- 3 Overview -- 4 Hierarchical Control.
5 Agent Model -- 5.1 Visual System -- 5.2 Blackboard System -- 5.3 Decision System -- 5.4 Animation System -- 6 Co-simulation System -- 6.1 Mode Switch -- 6.2 Inverse Kinematic -- 7 Results -- 7.1 Behaviour Simulation -- 7.2 Animation Simulation -- 7.3 User Study -- 8 Conclusion and Future Work -- References -- Towards Rendering the Style of 20th Century Cartoon Line Art in 3D Real-Time -- 1 Introduction -- 2 Related Works -- 2.1 Contour Extraction -- 2.2 Line Stylisation -- 2.3 Offline Rendering -- 3 Approaches -- 3.1 Edge Marking -- 3.2 Geometry Shader Line Rendering -- 3.3 Line Weight Map -- 3.4 Editing the Line Thickness in Real-Time -- 3.5 Recording Line Thickness in Real-Time Animation -- 4 Results -- 5 Conclusion and Future Works -- References -- Detection and Recognition -- Face Detection Algorithm in Classroom Scene Based on Deep Learning -- 1 Introduction -- 2 Related Works -- 2.1 Overview of Target Detection -- 2.2 Optical Flow Method -- 3 Proposed Method -- 3.1 Model Overview -- 3.2 Network Design -- 3.3 Improved Seq NMS -- 3.4 Face Count -- 4 Experience -- 4.1 Dataset -- 4.2 Pretreatment -- 4.3 Parameter Setting -- 4.4 Result -- 5 Conclusion -- References -- GRVT: Toward Effective Grocery Recognition via Vision Transformer -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Vision Transformer -- 3.2 GRVT Architecture -- 3.3 Multi-scale Patch Embedding -- 3.4 Mixed Attention Selection -- 4 Experiments -- 4.1 Datasets and Implementation Details -- 4.2 Comparison with the State of the Art -- 4.3 Ablation Study -- 4.4 Visualization -- 5 Conclusion -- References -- A Transformer-Based Cloth-Irrelevant Patches Feature Extracting Method for Long-Term Cloth-Changing Person Re-identification -- 1 Introduction -- 2 Related Work -- 2.1 Cloth-Changing Person Re-identification -- 2.2 Vision Transformer -- 2.3 Human Parsing -- 3 Methodology.
3.1 Transformer Encoder.
Record Nr. UNISA-996503467003316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in computer graphics : 39th computer graphics international conference, CGI 2022, virtual event, September 12-16, 2022, proceedings / / Nadia Magnenat-Thalmann [and six others], editors
Advances in computer graphics : 39th computer graphics international conference, CGI 2022, virtual event, September 12-16, 2022, proceedings / / Nadia Magnenat-Thalmann [and six others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (590 pages)
Disciplina 006.6869
Collana Lecture notes in computer science
Soggetto topico Computer graphics
ISBN 3-031-23473-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Image Analysis and Processing -- Multi-granularity Feature Attention Fusion Network for Image-Text Sentiment Analysis -- 1 Introduction -- 2 Related Work -- 2.1 Text Sentiment Analysis -- 2.2 Image Sentiment Analysis -- 2.3 Multimodal Sentiment Analysis -- 3 Our Proposed Model -- 3.1 Model Overview -- 3.2 Feature Learning Layer -- 3.3 Interactive Information Fusion Layer -- 3.4 Interactive Information Fusion Layer -- 4 Experimental Results -- 4.1 Dataset Description -- 4.2 Baselines -- 4.3 Experimental Results and Analysis -- 5 Conclusions -- References -- Toward Efficient Image Denoising: A Lightweight Network with Retargeting Supervision Driven Knowledge Distillation*-12pt -- 1 Introduction -- 2 Proposed Method -- 2.1 Lightweight U-shaped Denoising Network: LUNet -- 2.2 Retargeting Supervision Driven Knowledge Distillation -- 3 Experimental Results -- 3.1 Experimental Settings -- 3.2 Quantitative and Qualitative Results -- 3.3 Ablation Studies -- 4 Conclusions -- References -- A Pig Pose Estimation Model for Measuring Pig's Body Size -- 1 Introduction -- 2 Related Work -- 2.1 Measuring Animal Body Size -- 2.2 Key Point Identification -- 2.3 Attention Mechanism -- 3 Our Approach -- 3.1 Our Network Header -- 3.2 Down-Sampling Module -- 3.3 Selection of Key Points -- 4 Experiments -- 4.1 Dataset -- 4.2 Results on Image and Video -- 4.3 Results on Combining Attention Mechanism -- 4.4 Results on Using Our Network Header -- 5 Conclusion -- References -- Topology-Aware Learning for Semi-supervised Cross-domain Retinal Artery/Vein Classification*-12pt -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Spatial Transformation Module -- 2.3 Regional Mixing Module -- 2.4 Loss Function -- 3 Experimental Results -- 3.1 Datasets -- 3.2 Implementation Details -- 3.3 Artery/Vein Classification Performance.
4 Conclusion -- References -- Face Super-Resolution with Better Semantics and More Efficient Guidance -- 1 Introduction -- 2 Method -- 2.1 Overview of the Proposed Framework -- 2.2 Better Semantic Prior -- 2.3 More Efficient Guidance -- 2.4 Loss Functions -- 3 Experiments -- 3.1 Implementation Details -- 3.2 Comparisons with the State-of-the-Arts -- 3.3 Ablation Study -- 4 Conclusion -- References -- Graphs and Networks -- Layout and Display of Network Graphs on a Sphere*-12pt -- 1 Introduction -- 2 Related Work -- 3 Visualization Pipeline -- 4 Graph Visualization Algorithms -- 4.1 Layout - Adaptation of Fruchterman-Reingold Algorithm -- 4.2 Quantitative Evaluation -- 4.3 Visualizing Spheres in Paraview -- 4.4 Mathematical Basis for Visualizing Arcs in Paraview -- 5 Browser-Based Visualization -- 6 Conclusion -- References -- Joint Matrix Factorization and Structure Preserving for Domain Adaptation*-12pt -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Notations -- 3.2 Problem Formulation -- 3.3 Optimization -- 4 Experiments -- 4.1 Datasets Description -- 4.2 Results -- 4.3 Parameter Sensitivity and Ablation Study -- 5 Conclusion -- References -- Graph Adversarial Network with Bottleneck Adapter Tuning for Sign Language Production*-12pt -- 1 Introduction -- 2 Related Work -- 2.1 Sign Language Production -- 2.2 Transfer Learning -- 2.3 Graph Convolutional Network -- 3 Method -- 3.1 Adapter-Based Contextual Representation -- 3.2 Channel-Wise Target Length Predictor -- 3.3 Cross-modal Sign Pose Generator -- 3.4 Spatial-Temporal Graph Convolutional Discriminator -- 3.5 Loss Function -- 4 Experiments -- 4.1 Datasets -- 4.2 Training Settings -- 4.3 Evaluation Metrics -- 4.4 Quantitative Evaluation -- 4.5 Visual Comparison -- 4.6 Ablation Study -- 5 Conclusion -- References -- Estimation and Feature Matching.
Facial Landmarks Based Region-Level Data Augmentation for Gaze Estimation*-12pt -- 1 Introduction -- 2 Related Works -- 2.1 Gaze Estimation -- 2.2 Data Augmentation -- 3 Proposed Method -- 3.1 Facial Landmarks Based Region Mask -- 3.2 Non-eye Regions Data Augmentation -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Performance Comparison -- 4.3 Ablation Studies -- 5 Conclusions -- References -- An Efficient Dense Depth Map Estimation Algorithm Using Direct Stereo Matching for Ultra-Wide-Angle Images*-12pt -- 1 Introduction -- 2 Patch Matching Stereo -- 2.1 Camera Projection Model -- 2.2 Patch Matching Stereo for Ultra-Wide-Angle Images -- 3 Experimental Results -- 3.1 The TUM VI Benchmark -- 3.2 Comparisons -- 3.3 The Oxford RobotCar Dataset -- 4 Conclusion -- References -- Ad-RMS: Adaptive Regional Motion Statistics for Feature Matching Filtering -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Adaptive Regional Division -- 3.2 Regional Motion Statistics -- 4 Experiment -- 4.1 Evaluation -- 4.2 Dataset and Input Data -- 4.3 Parameters -- 4.4 Comparative Analysis of Results -- 5 Summary -- References -- 3D Reconstruction -- Visual Indoor Navigation Using Mobile Augmented Reality -- 1 Introduction -- 2 Related Work -- 2.1 Indoor Navigation System -- 2.2 Positioning and Navigation Technology -- 3 Research Content and Methodology -- 3.1 Plane and Point Cloud Detection and Visualization -- 3.2 Indoor Map Construction -- 3.3 Map Download and Self-positioning -- 3.4 Path Planning and Display -- 4 Experiment -- 5 Analysis of Results -- References -- Cost Volume Pyramid Network with Multi-strategies Range Searching for Multi-view Stereo -- 1 Introduction -- 2 Related Work -- 2.1 Coarse-to-Fine MVS Methods -- 2.2 Depth Sampling Range -- 2.3 Cost Volume -- 3 Methods -- 3.1 Overview -- 3.2 Depth Sampling Range Estimation -- 3.3 Supervise on Cost Volume.
3.4 Loss Function -- 4 Experiment -- 4.1 Dataset -- 4.2 Implementation Details -- 4.3 Results on DTU Dataset -- 4.4 Results on BlendedMVS -- 4.5 Effectiveness of Multi-strategies -- 4.6 Ablation Study -- 5 Conclusion -- References -- Reconstructing the Surface Mesh Representation for Single Neuron -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Branch Identification -- 3.2 Surface Reconstruction of Neurites -- 3.3 Surface Reconstruction of the Soma -- 4 Experiments and Results -- 5 Conclusion -- References -- WEmap: Weakness-Enhancement Mapping for 3D Reconstruction with Sparse Image Sequences -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Initial Reconstruction -- 3.2 Generation of the Enhanced Set -- 3.3 Reconstruction with Weighted Samples -- 4 Experiments -- 4.1 Datasets -- 4.2 Experiments on the Sparse DTU Dataset -- 4.3 Experiments on the Sparse Tanks and Temples Dataset -- 5 Conclusion -- References -- Rendering and Animation -- Comparing Traditional Rendering Techniques to Deep Learning Based Super-Resolution in Fire and Smoke Animations -- 1 Introduction -- 2 Related Work -- 3 TecoGAN -- 3.1 Network Architecture for Video Super-Resolution -- 3.2 Usage -- 4 Dataset Generation -- 4.1 Creating a Smoke Simulation -- 4.2 Multiple Simulations -- 5 Evaluation -- 5.1 Creating Different Renders -- 5.2 Comparing Video Quality -- 5.3 Cross Simulation Comparison -- 6 Conclusion -- References -- Real-Time Light Field Path Tracing -- 1 Introduction -- 2 Related Work -- 3 General Pipeline and Our Implementation -- 3.1 General Pipeline -- 3.2 Our Implementation -- 4 Experiments -- 5 Results -- 5.1 Runtime -- 5.2 Quality -- 6 Conclusions -- References -- Crowd Simulation with Detailed Body Motion and Interaction -- 1 Introduction -- 2 Related Work -- 2.1 Crowd Simulation -- 2.2 Motion Matching -- 3 Overview -- 4 Hierarchical Control.
5 Agent Model -- 5.1 Visual System -- 5.2 Blackboard System -- 5.3 Decision System -- 5.4 Animation System -- 6 Co-simulation System -- 6.1 Mode Switch -- 6.2 Inverse Kinematic -- 7 Results -- 7.1 Behaviour Simulation -- 7.2 Animation Simulation -- 7.3 User Study -- 8 Conclusion and Future Work -- References -- Towards Rendering the Style of 20th Century Cartoon Line Art in 3D Real-Time -- 1 Introduction -- 2 Related Works -- 2.1 Contour Extraction -- 2.2 Line Stylisation -- 2.3 Offline Rendering -- 3 Approaches -- 3.1 Edge Marking -- 3.2 Geometry Shader Line Rendering -- 3.3 Line Weight Map -- 3.4 Editing the Line Thickness in Real-Time -- 3.5 Recording Line Thickness in Real-Time Animation -- 4 Results -- 5 Conclusion and Future Works -- References -- Detection and Recognition -- Face Detection Algorithm in Classroom Scene Based on Deep Learning -- 1 Introduction -- 2 Related Works -- 2.1 Overview of Target Detection -- 2.2 Optical Flow Method -- 3 Proposed Method -- 3.1 Model Overview -- 3.2 Network Design -- 3.3 Improved Seq NMS -- 3.4 Face Count -- 4 Experience -- 4.1 Dataset -- 4.2 Pretreatment -- 4.3 Parameter Setting -- 4.4 Result -- 5 Conclusion -- References -- GRVT: Toward Effective Grocery Recognition via Vision Transformer -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Vision Transformer -- 3.2 GRVT Architecture -- 3.3 Multi-scale Patch Embedding -- 3.4 Mixed Attention Selection -- 4 Experiments -- 4.1 Datasets and Implementation Details -- 4.2 Comparison with the State of the Art -- 4.3 Ablation Study -- 4.4 Visualization -- 5 Conclusion -- References -- A Transformer-Based Cloth-Irrelevant Patches Feature Extracting Method for Long-Term Cloth-Changing Person Re-identification -- 1 Introduction -- 2 Related Work -- 2.1 Cloth-Changing Person Re-identification -- 2.2 Vision Transformer -- 2.3 Human Parsing -- 3 Methodology.
3.1 Transformer Encoder.
Record Nr. UNINA-9910639891803321
Cham, Switzerland : , : Springer, , [2022]
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Lo trovi qui: Univ. Federico II
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Advances in computer graphics : 38th Computer Graphics International Conference, CGI 2021, virtual event, September 6-10, 2021, proceedings / / edited by Nadia Magnenat-Thalmann [and six others]
Advances in computer graphics : 38th Computer Graphics International Conference, CGI 2021, virtual event, September 6-10, 2021, proceedings / / edited by Nadia Magnenat-Thalmann [and six others]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (717 pages)
Disciplina 006.6
Collana Lecture Notes in Computer Science
Soggetto topico Computer graphics
ISBN 3-030-89029-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Computer Animation -- Temporal Parameter-Free Deep Skinning of Animated Meshes -- 1 Introduction -- 2 Related Work -- 3 Temporal Deep Skinning -- 3.1 Training and Test Datasets -- 3.2 Transformation and Weight Optimization -- 3.3 Measuring the Error -- 3.4 Building and Tuning a Neural Network for Weight Prediction -- 4 Experimental Evaluation of Deep Skinning -- 4.1 Quantitative Results -- 4.2 Visual Quality Evaluation Results -- 4.3 Discussion and Applications -- 5 Conclusions -- A Appendix A -- B Appendix B -- C Appendix C -- References -- The Impact of Animations in the Perception of a Simulated Crowd -- 1 Introduction -- 2 Related Work -- 2.1 Appearance and Motion of Virtual Humans -- 2.2 Crowd Simulation -- 3 Experiment Design -- 3.1 Stimuli Creation -- 3.2 Participants -- 3.3 Hypothesis -- 3.4 Statistical Analysis -- 4 Results -- 4.1 Realism of Simulated Crowds (H1) -- 4.2 Realism of Trajectories (H2) -- 4.3 Realism of Animation (H3) -- 5 Discussion -- 6 Conclusions and Future Work -- References -- Computer Vision -- Virtual Haptic System for Shape Recognition Based on Local Curvatures -- 1 Introduction -- 2 Related Work -- 3 Data Capture -- 3.1 Stimuli -- 3.2 Data Collection -- 4 Classifiers -- 4.1 Probability Density Function Based -- 4.2 Bayesian XGBoost -- 5 Results -- 5.1 Probability Density Function Based -- 5.2 Bayesian XGBoost -- 6 Discussion -- 7 Conclusions and Future Work -- References -- Stable Depth Estimation Within Consecutive Video Frames -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Temporal Stability Loss -- 3.2 Inconsistency Check and Self-discovered Mask -- 3.3 De-scaled Geometry Consistency Loss -- 3.4 Network Architecture -- 4 Experiments -- 4.1 Training Details -- 4.2 Comparisons and Ablation Study -- 5 Conclusions and Future Work -- References.
Progressive Multi-scale Reconstruction for Guided Depth Map Super-Resolution via Deep Residual Gate Fusion Network -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Overview -- 3.2 Color Information Extraction Branch -- 3.3 Depth Map Super-Resolution Branch -- 3.4 Loss Function -- 4 Experimental Results -- 4.1 Implementation Details -- 4.2 Quantitative Evaluation -- 4.3 Qualitative Evaluation -- 5 Conclusion -- References -- SE_EDNet: A Robust Manipulated Faces Detection Algorithm -- 1 Introduction -- 2 Detection Algorithms -- 2.1 Framework -- 2.2 Network Structure -- 2.3 Image Residuals in YCrCb Color Space -- 3 Experiment Analysis -- 3.1 Setup -- 3.2 Comparison Experiment -- 3.3 Robustness Performance Analysis -- 4 Conclusion -- References -- PointCNN-Based Individual Tree Detection Using LiDAR Point Clouds -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Build CHM -- 2.3 Generate Detection Sample -- 2.4 Sample Classifier -- 2.5 Tree Stagger Analysis -- 3 Results -- 3.1 Detection Result -- 3.2 Comparison with Related Research -- 4 Conclusion -- References -- Variance Weight Distribution Network Based Noise Sample Learning for Robust Person Re-identification -- 1 Introduction -- 2 Related Work -- 2.1 Deep Person Re-ID Models -- 2.2 Person Re-ID with Sample Noise -- 2.3 Robust Deep Learning with Label Noise -- 2.4 Feature Distribution Modelling -- 3 Methodology -- 3.1 Conventional Baseline Model -- 3.2 Feature Uncertainty Distribution Learning -- 3.3 Rectifying Label Learning -- 3.4 Overall Classification Loss -- 4 Experiments -- 4.1 Datasets and Settings -- 4.2 Implementation Details -- 4.3 Comparison with the State-of-the-Arts -- 5 Conclusion -- References -- Monocular Dense SLAM with Consistent Deep Depth Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Monocular Visual SLAM -- 2.2 Dense Mapping.
2.3 SLAM with Deep Depth Prediction -- 3 System Overview -- 4 Local Mapping with Depth Refinement -- 4.1 2D Image Analysis -- 4.2 3D Outlier Detection -- 5 Global Dense Mapping with Egomotion Constraints -- 6 Evaluation -- 6.1 Qualitative Results -- 6.2 Quantitative Results -- 7 Conclusion -- References -- 3D Shape-Adapted Garment Generation with Sketches -- 1 Introduction -- 2 Related Work -- 3 The Proposed Method -- 3.1 Overview of the Network Architecture -- 3.2 Sketch Encoder and Body Shape Encoder -- 3.3 Fully Convolutional Mesh Decoder -- 3.4 Loss Function -- 4 Experiments -- 4.1 Dataset Construction -- 4.2 Results -- 5 Conclusion -- References -- Geometric Computing -- Light-Weight Multi-view Topology Consistent Facial Geometry and Reflectance Capture -- 1 Introduction -- 2 Related Work -- 2.1 High-Quality Facial Geometry -- 2.2 Facial Appearance Capture -- 3 System Overview -- 4 Proposed Method -- 4.1 Landmarks Based Initialization -- 4.2 Mesh Deformation -- 4.3 Multi-view Based Diffuse-Specular Separation -- 4.4 Surface Normal and BRDF Estimation -- 4.5 Finer Geometry Optimization -- 5 Results -- 6 Conclusion -- References -- Real-Time Fluid Simulation with Atmospheric Pressure Using Weak Air Particles -- 1 Introduction -- 2 Related Work -- 2.1 Particle-Based Fluid Simulation -- 2.2 Fluid Simulation with Atmospheric Pressure -- 3 Background -- 4 Weak Air Particles -- 5 Surface Force Model -- 5.1 Density-Related Atmospheric Pressure Force -- 5.2 Surface Tension Force -- 6 Implementation -- 7 Results -- 8 Conclusion and Future Work -- References -- Human Poses and Gestures -- Reinforcement Learning for Quadruped Locomotion -- 1 Introduction -- 1.1 Objectives -- 1.2 Analytic Reviews on Previous Work -- 2 Methodology -- 2.1 Modelling Quadruped Locomotion -- 2.2 Reinforcement Learning -- 3 Experiment and Comparative Evaluation.
4 Discussion and Conclusion -- References -- Partially Occluded Skeleton Action Recognition Based on Multi-stream Fusion Graph Convolutional Networks -- 1 Introduction -- 2 Related Work -- 2.1 Manual Feature Extraction Method -- 2.2 RNN/CNN-Based Method -- 2.3 GCN-Based Method -- 3 Proposed Method -- 3.1 Multimodal Feature Extraction -- 3.2 Spatial-Temporal Graph Convolutional Network -- 3.3 Occlusion Sensitive Multi-stream Fusion Networks -- 4 Experiments -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Experimental Results -- 5 Conclusion -- References -- Social-Scene-Aware Generative Adversarial Networks for Pedestrian Trajectory Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Crowd Interaction -- 2.2 Multimodal Trajectory Prediction -- 3 Method -- 3.1 The Formulation for Pedestrian Trajectory Prediction -- 3.2 Scene Module -- 3.3 Social Module -- 3.4 Generative Adversarial Networks Module -- 4 Experiments -- 4.1 Evaluation Metrics and Baselines -- 4.2 Quantitative Evaluations -- 4.3 Qualitative Evaluations -- 5 Conclusion -- References -- Image Processing -- Cecid Fly Defect Detection in Mangoes Using Object Detection Frameworks -- 1 Introduction -- 2 Towards Automatic Defect Detection in Agricultural Produce -- 3 Methodology -- 3.1 Image Acquisition -- 3.2 Data Preparation -- 3.3 Object Detection Frameworks -- 4 Experimental Results -- 5 Conclusion and Future Works -- References -- Twin-Channel Gan: Repair Shape with Twin-Channel Generative Adversarial Network and Structural Constraints*-6pt -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Geometry Information Completion -- 3.2 Structure Information Optimization -- 3.3 Fine-Tune -- 4 Experiments and Evaluation -- 4.1 Implementation Details -- 4.2 Shape Repair -- 4.3 Results and Discussion -- 5 Limitation and Future Work -- 6 Conclusion -- References.
CoPaint: Guiding Sketch Painting with Consistent Color and Coherent Generative Adversarial Networks -- 1 Introduction -- 2 Related Work -- 2.1 Generative Adversarial Networks (GANs) -- 2.2 Colorization -- 3 Methods -- 3.1 Overview -- 3.2 Dataset -- 3.3 Network Structure -- 3.4 Loss Function -- 4 Experiments -- 4.1 Training Strategy -- 4.2 Dataset Generation -- 4.3 Analysis on Angles -- 5 Evaluation -- 5.1 Quality Analysis -- 5.2 Color Consistency Analysis -- 5.3 Ablation Studies -- 6 Conclusions and Limitations -- References -- Multi-Stream Fusion Network for Multi-Distortion Image Super-Resolution -- 1 Introduction -- 2 Method -- 2.1 Multi-Stream Fusion -- 2.2 Fusion Module -- 2.3 Deep Supervision -- 3 Experimental Results -- 3.1 Data Preprocessing and Network Training -- 3.2 Model Analysis -- 3.3 Results Analysis -- 4 Conclusion -- References -- Generative Face Parsing Map Guided 3D Face Reconstruction Under Occluded Scenes -- 1 Introduction -- 2 Related Works -- 2.1 Generic Face Reconstruction -- 2.2 Face Image Synthesis -- 3 Our Approach -- 3.1 Landmark Prediction Task -- 3.2 Face Parsing Map Generation -- 3.3 Face Image Synthesis with GAN -- 3.4 Camera and Illumination Model -- 3.5 Loss Function of 3D Reconstruction -- 4 Implementation Details -- 5 Experimental Results -- 5.1 Qualitative Comparisons with Recent Works -- 5.2 Quantitative Comparison -- 6 Conclusions -- References -- Compact Double Attention Module Embedded CNN for Palmprint Recognition -- 1 Introduction -- 2 Related Work -- 2.1 CNN-Based Palmprint Recognition Methods -- 2.2 Attention Mechanism -- 3 The Proposed Method -- 3.1 The Framework of CDAM-Net -- 3.2 Double Attention Module (DAM) -- 4 Experiments -- 4.1 Databases -- 4.2 Palmprint Identification Results -- 4.3 Effectiveness of the DAM -- 4.4 Parameter Analysis -- 5 Conclusion -- References.
M2M: Learning to Enhance Low-Light Image from Model to Mobile FPGA.
Record Nr. UNISA-996464484503316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in computer graphics : 38th Computer Graphics International Conference, CGI 2021, virtual event, September 6-10, 2021, proceedings / / edited by Nadia Magnenat-Thalmann [and six others]
Advances in computer graphics : 38th Computer Graphics International Conference, CGI 2021, virtual event, September 6-10, 2021, proceedings / / edited by Nadia Magnenat-Thalmann [and six others]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (717 pages)
Disciplina 006.6
Collana Lecture Notes in Computer Science
Soggetto topico Computer graphics
ISBN 3-030-89029-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Computer Animation -- Temporal Parameter-Free Deep Skinning of Animated Meshes -- 1 Introduction -- 2 Related Work -- 3 Temporal Deep Skinning -- 3.1 Training and Test Datasets -- 3.2 Transformation and Weight Optimization -- 3.3 Measuring the Error -- 3.4 Building and Tuning a Neural Network for Weight Prediction -- 4 Experimental Evaluation of Deep Skinning -- 4.1 Quantitative Results -- 4.2 Visual Quality Evaluation Results -- 4.3 Discussion and Applications -- 5 Conclusions -- A Appendix A -- B Appendix B -- C Appendix C -- References -- The Impact of Animations in the Perception of a Simulated Crowd -- 1 Introduction -- 2 Related Work -- 2.1 Appearance and Motion of Virtual Humans -- 2.2 Crowd Simulation -- 3 Experiment Design -- 3.1 Stimuli Creation -- 3.2 Participants -- 3.3 Hypothesis -- 3.4 Statistical Analysis -- 4 Results -- 4.1 Realism of Simulated Crowds (H1) -- 4.2 Realism of Trajectories (H2) -- 4.3 Realism of Animation (H3) -- 5 Discussion -- 6 Conclusions and Future Work -- References -- Computer Vision -- Virtual Haptic System for Shape Recognition Based on Local Curvatures -- 1 Introduction -- 2 Related Work -- 3 Data Capture -- 3.1 Stimuli -- 3.2 Data Collection -- 4 Classifiers -- 4.1 Probability Density Function Based -- 4.2 Bayesian XGBoost -- 5 Results -- 5.1 Probability Density Function Based -- 5.2 Bayesian XGBoost -- 6 Discussion -- 7 Conclusions and Future Work -- References -- Stable Depth Estimation Within Consecutive Video Frames -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Temporal Stability Loss -- 3.2 Inconsistency Check and Self-discovered Mask -- 3.3 De-scaled Geometry Consistency Loss -- 3.4 Network Architecture -- 4 Experiments -- 4.1 Training Details -- 4.2 Comparisons and Ablation Study -- 5 Conclusions and Future Work -- References.
Progressive Multi-scale Reconstruction for Guided Depth Map Super-Resolution via Deep Residual Gate Fusion Network -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Overview -- 3.2 Color Information Extraction Branch -- 3.3 Depth Map Super-Resolution Branch -- 3.4 Loss Function -- 4 Experimental Results -- 4.1 Implementation Details -- 4.2 Quantitative Evaluation -- 4.3 Qualitative Evaluation -- 5 Conclusion -- References -- SE_EDNet: A Robust Manipulated Faces Detection Algorithm -- 1 Introduction -- 2 Detection Algorithms -- 2.1 Framework -- 2.2 Network Structure -- 2.3 Image Residuals in YCrCb Color Space -- 3 Experiment Analysis -- 3.1 Setup -- 3.2 Comparison Experiment -- 3.3 Robustness Performance Analysis -- 4 Conclusion -- References -- PointCNN-Based Individual Tree Detection Using LiDAR Point Clouds -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Build CHM -- 2.3 Generate Detection Sample -- 2.4 Sample Classifier -- 2.5 Tree Stagger Analysis -- 3 Results -- 3.1 Detection Result -- 3.2 Comparison with Related Research -- 4 Conclusion -- References -- Variance Weight Distribution Network Based Noise Sample Learning for Robust Person Re-identification -- 1 Introduction -- 2 Related Work -- 2.1 Deep Person Re-ID Models -- 2.2 Person Re-ID with Sample Noise -- 2.3 Robust Deep Learning with Label Noise -- 2.4 Feature Distribution Modelling -- 3 Methodology -- 3.1 Conventional Baseline Model -- 3.2 Feature Uncertainty Distribution Learning -- 3.3 Rectifying Label Learning -- 3.4 Overall Classification Loss -- 4 Experiments -- 4.1 Datasets and Settings -- 4.2 Implementation Details -- 4.3 Comparison with the State-of-the-Arts -- 5 Conclusion -- References -- Monocular Dense SLAM with Consistent Deep Depth Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Monocular Visual SLAM -- 2.2 Dense Mapping.
2.3 SLAM with Deep Depth Prediction -- 3 System Overview -- 4 Local Mapping with Depth Refinement -- 4.1 2D Image Analysis -- 4.2 3D Outlier Detection -- 5 Global Dense Mapping with Egomotion Constraints -- 6 Evaluation -- 6.1 Qualitative Results -- 6.2 Quantitative Results -- 7 Conclusion -- References -- 3D Shape-Adapted Garment Generation with Sketches -- 1 Introduction -- 2 Related Work -- 3 The Proposed Method -- 3.1 Overview of the Network Architecture -- 3.2 Sketch Encoder and Body Shape Encoder -- 3.3 Fully Convolutional Mesh Decoder -- 3.4 Loss Function -- 4 Experiments -- 4.1 Dataset Construction -- 4.2 Results -- 5 Conclusion -- References -- Geometric Computing -- Light-Weight Multi-view Topology Consistent Facial Geometry and Reflectance Capture -- 1 Introduction -- 2 Related Work -- 2.1 High-Quality Facial Geometry -- 2.2 Facial Appearance Capture -- 3 System Overview -- 4 Proposed Method -- 4.1 Landmarks Based Initialization -- 4.2 Mesh Deformation -- 4.3 Multi-view Based Diffuse-Specular Separation -- 4.4 Surface Normal and BRDF Estimation -- 4.5 Finer Geometry Optimization -- 5 Results -- 6 Conclusion -- References -- Real-Time Fluid Simulation with Atmospheric Pressure Using Weak Air Particles -- 1 Introduction -- 2 Related Work -- 2.1 Particle-Based Fluid Simulation -- 2.2 Fluid Simulation with Atmospheric Pressure -- 3 Background -- 4 Weak Air Particles -- 5 Surface Force Model -- 5.1 Density-Related Atmospheric Pressure Force -- 5.2 Surface Tension Force -- 6 Implementation -- 7 Results -- 8 Conclusion and Future Work -- References -- Human Poses and Gestures -- Reinforcement Learning for Quadruped Locomotion -- 1 Introduction -- 1.1 Objectives -- 1.2 Analytic Reviews on Previous Work -- 2 Methodology -- 2.1 Modelling Quadruped Locomotion -- 2.2 Reinforcement Learning -- 3 Experiment and Comparative Evaluation.
4 Discussion and Conclusion -- References -- Partially Occluded Skeleton Action Recognition Based on Multi-stream Fusion Graph Convolutional Networks -- 1 Introduction -- 2 Related Work -- 2.1 Manual Feature Extraction Method -- 2.2 RNN/CNN-Based Method -- 2.3 GCN-Based Method -- 3 Proposed Method -- 3.1 Multimodal Feature Extraction -- 3.2 Spatial-Temporal Graph Convolutional Network -- 3.3 Occlusion Sensitive Multi-stream Fusion Networks -- 4 Experiments -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Experimental Results -- 5 Conclusion -- References -- Social-Scene-Aware Generative Adversarial Networks for Pedestrian Trajectory Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Crowd Interaction -- 2.2 Multimodal Trajectory Prediction -- 3 Method -- 3.1 The Formulation for Pedestrian Trajectory Prediction -- 3.2 Scene Module -- 3.3 Social Module -- 3.4 Generative Adversarial Networks Module -- 4 Experiments -- 4.1 Evaluation Metrics and Baselines -- 4.2 Quantitative Evaluations -- 4.3 Qualitative Evaluations -- 5 Conclusion -- References -- Image Processing -- Cecid Fly Defect Detection in Mangoes Using Object Detection Frameworks -- 1 Introduction -- 2 Towards Automatic Defect Detection in Agricultural Produce -- 3 Methodology -- 3.1 Image Acquisition -- 3.2 Data Preparation -- 3.3 Object Detection Frameworks -- 4 Experimental Results -- 5 Conclusion and Future Works -- References -- Twin-Channel Gan: Repair Shape with Twin-Channel Generative Adversarial Network and Structural Constraints*-6pt -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Geometry Information Completion -- 3.2 Structure Information Optimization -- 3.3 Fine-Tune -- 4 Experiments and Evaluation -- 4.1 Implementation Details -- 4.2 Shape Repair -- 4.3 Results and Discussion -- 5 Limitation and Future Work -- 6 Conclusion -- References.
CoPaint: Guiding Sketch Painting with Consistent Color and Coherent Generative Adversarial Networks -- 1 Introduction -- 2 Related Work -- 2.1 Generative Adversarial Networks (GANs) -- 2.2 Colorization -- 3 Methods -- 3.1 Overview -- 3.2 Dataset -- 3.3 Network Structure -- 3.4 Loss Function -- 4 Experiments -- 4.1 Training Strategy -- 4.2 Dataset Generation -- 4.3 Analysis on Angles -- 5 Evaluation -- 5.1 Quality Analysis -- 5.2 Color Consistency Analysis -- 5.3 Ablation Studies -- 6 Conclusions and Limitations -- References -- Multi-Stream Fusion Network for Multi-Distortion Image Super-Resolution -- 1 Introduction -- 2 Method -- 2.1 Multi-Stream Fusion -- 2.2 Fusion Module -- 2.3 Deep Supervision -- 3 Experimental Results -- 3.1 Data Preprocessing and Network Training -- 3.2 Model Analysis -- 3.3 Results Analysis -- 4 Conclusion -- References -- Generative Face Parsing Map Guided 3D Face Reconstruction Under Occluded Scenes -- 1 Introduction -- 2 Related Works -- 2.1 Generic Face Reconstruction -- 2.2 Face Image Synthesis -- 3 Our Approach -- 3.1 Landmark Prediction Task -- 3.2 Face Parsing Map Generation -- 3.3 Face Image Synthesis with GAN -- 3.4 Camera and Illumination Model -- 3.5 Loss Function of 3D Reconstruction -- 4 Implementation Details -- 5 Experimental Results -- 5.1 Qualitative Comparisons with Recent Works -- 5.2 Quantitative Comparison -- 6 Conclusions -- References -- Compact Double Attention Module Embedded CNN for Palmprint Recognition -- 1 Introduction -- 2 Related Work -- 2.1 CNN-Based Palmprint Recognition Methods -- 2.2 Attention Mechanism -- 3 The Proposed Method -- 3.1 The Framework of CDAM-Net -- 3.2 Double Attention Module (DAM) -- 4 Experiments -- 4.1 Databases -- 4.2 Palmprint Identification Results -- 4.3 Effectiveness of the DAM -- 4.4 Parameter Analysis -- 5 Conclusion -- References.
M2M: Learning to Enhance Low-Light Image from Model to Mobile FPGA.
Record Nr. UNINA-9910502612303321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui