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[null,"1.","Record Nr.",null,"UNISA996503467003316"]
[null,null,"Titolo",null,"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"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-031-23473-1"]
[null,null,"Descrizione fisica",null,"1 online resource (590 pages)"]
[null,null,"Collana",null,"Lecture notes in computer science ; ; Volume 13443"]
[null,null,"Disciplina",null,"006.6869"]
[null,null,"Soggetti",null,"Computer graphics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"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 -- "]
[{"$nulls":4},"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."]
[{"$nulls":4},"4 Conclusion -- References -- Face Super-Resolution with Better Semantics and More Efficient Guidance -- 1 Introduction -- 2 Method -- 2.1 Overview of the Proposed Framework -- 2.2 Better Semantic Prior -- 2.3 More Efficient Guidance -- 2.4 Loss Functions -- 3 Experiments -- 3.1 Implementation Details -- 3.2 Comparisons with the State-of-the-Arts -- 3.3 Ablation Study -- 4 Conclusion -- References -- Graphs and Networks -- Layout and Display of Network Graphs on a Sphere*-12pt -- 1 Introduction -- 2 Related Work -- 3 Visualization Pipeline -- 4 Graph Visualization Algorithms -- 4.1 Layout - Adaptation of Fruchterman-Reingold Algorithm -- 4.2 Quantitative Evaluation -- 4.3 Visualizing Spheres in Paraview -- 4.4 Mathematical Basis for Visualizing Arcs in Paraview -- 5 Browser-Based Visualization -- 6 Conclusion -- References -- Joint Matrix Factorization and Structure Preserving for Domain Adaptation*-12pt -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Notations -- 3.2 Problem Formulation -- 3.3 Optimization -- 4 Experiments -- 4.1 Datasets Description -- 4.2 Results -- 4.3 Parameter Sensitivity and Ablation Study -- 5 Conclusion -- References -- Graph Adversarial Network with Bottleneck Adapter Tuning for Sign Language Production*-12pt -- 1 Introduction -- 2 Related Work -- 2.1 Sign Language Production -- 2.2 Transfer Learning -- 2.3 Graph Convolutional Network -- 3 Method -- 3.1 Adapter-Based Contextual Representation -- 3.2 Channel-Wise Target Length Predictor -- 3.3 Cross-modal Sign Pose Generator -- 3.4 Spatial-Temporal Graph Convolutional Discriminator -- 3.5 Loss Function -- 4 Experiments -- 4.1 Datasets -- 4.2 Training Settings -- 4.3 Evaluation Metrics -- 4.4 Quantitative Evaluation -- 4.5 Visual Comparison -- 4.6 Ablation Study -- 5 Conclusion -- References -- Estimation and Feature Matching."]
[{"$nulls":4},"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 "]
[{"$nulls":4},"Range -- 2.3 Cost Volume -- 3 Methods -- 3.1 Overview -- 3.2 Depth Sampling Range Estimation -- 3.3 Supervise on Cost Volume."]
[{"$nulls":4},"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."]
[{"$nulls":4},"5 Agent Model -- 5.1 Visual System -- 5.2 Blackboard System -- 5.3 Decision System -- 5.4 Animation System -- 6 Co-simulation System -- 6.1 Mode Switch -- 6.2 Inverse Kinematic -- 7 Results -- 7.1 Behaviour Simulation -- 7.2 Animation Simulation -- 7.3 User Study -- 8 Conclusion and Future Work -- References -- Towards Rendering the Style of 20th Century Cartoon Line Art in 3D Real-Time -- 1 Introduction -- 2 Related Works -- 2.1 Contour Extraction -- 2.2 Line Stylisation -- 2.3 Offline Rendering -- 3 Approaches -- 3.1 Edge Marking -- 3.2 Geometry Shader Line Rendering -- 3.3 Line Weight Map -- 3.4 Editing the Line Thickness in Real-Time -- 3.5 Recording Line Thickness in Real-Time Animation -- 4 Results -- 5 Conclusion and Future Works -- References -- Detection and Recognition -- Face Detection Algorithm in Classroom Scene Based on Deep Learning -- 1 Introduction -- 2 Related Works -- 2.1 Overview of Target Detection -- 2.2 Optical Flow Method -- 3 Proposed Method -- 3.1 Model Overview -- 3.2 Network Design -- 3.3 Improved Seq NMS -- 3.4 Face Count -- 4 Experience -- 4.1 Dataset -- 4.2 Pretreatment -- 4.3 Parameter Setting -- 4.4 Result -- 5 Conclusion -- References -- GRVT: Toward Effective Grocery Recognition via Vision Transformer -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Vision Transformer -- 3.2 GRVT Architecture -- 3.3 Multi-scale Patch Embedding -- 3.4 Mixed Attention Selection -- 4 Experiments -- 4.1 Datasets and Implementation Details -- 4.2 Comparison with the State of the Art -- 4.3 Ablation Study -- 4.4 Visualization -- 5 Conclusion -- References -- A Transformer-Based Cloth-Irrelevant Patches Feature Extracting Method for Long-Term Cloth-Changing Person Re-identification -- 1 Introduction -- 2 Related Work -- 2.1 Cloth-Changing Person Re-"]
[{"$nulls":4},"identification -- 2.2 Vision Transformer -- 2.3 Human Parsing -- 3 Methodology."]
[{"$nulls":4},"3.1 Transformer Encoder."]
[null,"2.","Record Nr.",null,"UNISALENTO991004047919707536"]
[null,null,"Autore",null,"Campigli, Francesca"]
[null,null,"Titolo",null,"Un cammino a ostacoli : neocatecumenali e Chiesa di Roma / Francesca Campigli"]
[null,null,"Pubbl/distr/stampa",null,"Firenze : Firenze University press, 2018"]
[null,null,"ISBN",null,"9788864538877"]
[null,null,"Descrizione fisica",null,"211 p. ; 24 cm"]
[null,null,"Collana",null,"Premio Istituto Sangalli per la storia religiosa ; 5"]
[null,null,"Disciplina",null,"265.13"]
[null,null,"Soggetti",null,"Neocatecumenali"]
[null,null,"Lingua di pubblicazione",null,"Non definito"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","In copertina: Premio Istituto Sangalli 2017"]
[null,"3.","Record Nr.",null,"UNINA9910786096003321"]
[null,null,"Autore",null,"Greeley Ronald"]
[null,null,"Titolo",null,"Introduction to planetary geomorphology / / Ronald Greeley [[electronic resource]]"]
[null,null,"Pubbl/distr/stampa",null,"Cambridge : , : Cambridge University Press, , 2013"]
[null,null,"ISBN",null,"1-316-08912-6"]
[{"$nulls":4},"1-139-56400-5"]
[{"$nulls":4},"1-139-55412-3"]
[{"$nulls":4},"1-139-55041-1"]
[{"$nulls":4},"1-283-94800-1"]
[{"$nulls":4},"1-139-54916-2"]
[{"$nulls":4},"1-139-55537-5"]
[{"$nulls":4},"1-139-02096-X"]
[{"$nulls":4},"1-139-55166-3"]
[null,null,"Descrizione fisica",null,"1 online resource (xiii, 238 pages) : digital, PDF file(s)"]
[null,null,"Classificazione",null,"SCI004000"]
[null,null,"Disciplina",null,"551.410999/2"]
[null,null,"Soggetti",null,"Planets - Geology"]
[{"$nulls":4},"Planets - Crust"]
[{"$nulls":4},"Geomorphology"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Title from publisher's bibliographic system (viewed on 05 Oct 2015)."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Cover; Contents; Foreword; Preface; Acknowledgments; Chapter 1 Introduction; 1.1 Solar System overview; 1.1.1 The terrestrial planets; 1.1.2 The giant planets; 1.1.3 Small bodies, Pluto, and \"dwarf planets\"; 1.2 Objectives of Solar System exploration; 1.2.1 Planetary geology objectives; 1.2.2 Astrobiology; 1.3 Strategy for Solar System exploration; 1.4 Flight projects; 1.5 Planetary data; 1.6 Planetary research results; Assignments; Chapter 2 Planetary geomorphology methods; 2.1 Introduction; 2.2 Approach; 2.3 Planetary geologic maps; 2.4 Geologic time; 2.5 Remote sensing data"]
[{"$nulls":4},"2.5.1 Visible imaging data2.5.2 Multispectral data; 2.5.3 Thermal data; 2.5.4 Radar imaging data; 2.5.5 Ultraviolet, X-ray, and gamma-ray data; 2.6 Geophysical data; 2.7 Image processing; 2.8 Resolution; 2.9 Electronic data records (EDRs); 2.10 Cartography; Assignments; Chapter 3 Planetary morphologic processes; 3.1 Introduction; 3.2 Tectonism; 3.3 Volcanic processes; 3.3.1 Volcanic eruptions; 3.3.2 "]
[{"$nulls":4},"Volcanic morphology; 3.3.3 Volcanic craters; 3.3.4 Intrusive structures; 3.4 Impact cratering; 3.4.1 Impact cratering mechanics; 3.4.2 Impact craters on Earth"]
[{"$nulls":4},"3.4.3 Impact craters and planetary environments3.5 Gradation; 3.5.1 Weathering; 3.5.2 Mass wasting; 3.5.3 Processes associated with the hydrologic cycle; 3.5.4 Aeolian processes; 3.5.5 Periglacial processes; 3.6 Summary; Assignments; Chapter 4 Earth's Moon; 4.1 Introduction; 4.2 Lunar exploration; 4.2.1 Pre-Apollo studies; 4.2.2 The Apollo era; 4.2.3 Post-Apollo exploration; 4.3 Interior characteristics; 4.4 Surface composition; 4.5 Geomorphology; 4.5.1 Impact craters and basins; 4.5.2 Highland plains; 4.5.3 Mare terrains; 4.5.4 Sinuous rilles; 4.5.5 Volcanic constructs"]
[{"$nulls":4},"4.5.6 Tectonic features4.5.7 Gradational features; 4.6 Geologic history of the Moon; Assignments; Chapter 5 Mercury; 5.1 Introduction; 5.2 Mercury exploration; 5.3 Interior characteristics; 5.4 Surface composition; 5.5 Geomorphology; 5.5.1 General physiography; 5.5.2 Impact craters; 5.5.3 Multi-ring basins; 5.5.4 Volcanic features; 5.5.5 Tectonic features; 5.5.6 Gradation features; 5.6 Geologic history; Assignments; Chapter 6 Venus; 6.1 Introduction; 6.2 Venus exploration; 6.3 Interior characteristics; 6.4 Surface compositions; 6.5 Geomorphology; 6.5.1 General physiography"]
[{"$nulls":4},"6.5.2 Impact craters6.5.3 Volcanic features; 6.5.4 Tectonic features; 6.5.5 Gradation features; 6.6 Geologic history; Assignments; Chapter 7 Mars; 7.1 Introduction; 7.2 Exploration; 7.3 Interior; 7.4 Surface composition; 7.5 Geomorphology; 7.5.1 Physiography; 7.5.2 Impact craters; 7.5.3 Volcanic features; 7.5.4 Tectonic features; 7.5.5 Gradation features; 7.6 Geologic history; Assignments; Chapter 8 The Jupiter system; 8.1 Introduction; 8.2 Exploration; 8.3 Jupiter; 8.4 Io; 8.4.1 Impact features (none!); 8.4.2 Volcanic features; 8.4.3 Tectonic features; 8.4.4 Gradation features"]
[{"$nulls":4},"8.4.5 Io summary"]
[null,null,null,"Sommario/riassunto","Nearly all major planets and moons in our Solar System have been visited by spacecraft and the data they have returned has revealed the incredible diversity of planetary surfaces. Featuring a wealth of images, this textbook explores the geological evolution of the planets and moons. Introductory chapters discuss how information gathered from spacecraft is used to unravel the geological complexities of our Solar System. Subsequent chapters focus on current understandings of planetary systems. The textbook shows how planetary images and remote sensing data are analyzed through the application of fundamental geological principles. It draws on results from spacecraft sent throughout the Solar System by NASA and other space agencies. Aimed at undergraduate students in planetary geology, geoscience, astronomy and solar system science, it highlights the differences and similarities of the surfaces at a level that can be readily understood by non-specialists."]