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MARC Lista (tabellare)
Advances in Computer Graphics [[electronic resource] ] : 36th Computer Graphics International Conference, CGI 2019, Calgary, AB, Canada, June 17–20, 2019, Proceedings / / edited by Marina Gavrilova, Jian Chang, Nadia Magnenat Thalmann, Eckhard Hitzer, Hiroshi Ishikawa
Advances in Computer Graphics [[electronic resource] ] : 36th Computer Graphics International Conference, CGI 2019, Calgary, AB, Canada, June 17–20, 2019, Proceedings / / edited by Marina Gavrilova, Jian Chang, Nadia Magnenat Thalmann, Eckhard Hitzer, Hiroshi Ishikawa
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (XV, 587 p. 384 illus., 274 illus. in color.)
Disciplina 004
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Application software
Computer vision
User interfaces (Computer systems)
Human-computer interaction
Computer graphics
Artificial intelligence
Computer engineering
Computer networks
Computer and Information Systems Applications
Computer Vision
User Interfaces and Human Computer Interaction
Computer Graphics
Artificial Intelligence
Computer Engineering and Networks
ISBN 3-030-22514-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 3D Reconstruction and Rendering -- Virtual Reality and Augmented Reality -- Computer Animation -- Geometric Modelling -- Geometric Computing -- Shape and Surface Modelling -- Visual Analytics -- Image Processing -- Pattern Recognition -- Motion Planning -- Gait and Activity Biometric Recognition -- Machine Learning for Graphics and Applications in Security -- Smart Electronics -- Autonomous Navigation Systems -- Robotics -- Geographical Information Systems -- Medicine and Art.
Record Nr. UNISA-996466326203316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
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Advances in Computer Graphics : 36th Computer Graphics International Conference, CGI 2019, Calgary, AB, Canada, June 17–20, 2019, Proceedings / / edited by Marina Gavrilova, Jian Chang, Nadia Magnenat Thalmann, Eckhard Hitzer, Hiroshi Ishikawa
Advances in Computer Graphics : 36th Computer Graphics International Conference, CGI 2019, Calgary, AB, Canada, June 17–20, 2019, Proceedings / / edited by Marina Gavrilova, Jian Chang, Nadia Magnenat Thalmann, Eckhard Hitzer, Hiroshi Ishikawa
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (XV, 587 p. 384 illus., 274 illus. in color.)
Disciplina 004
006.6
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Application software
Computer vision
User interfaces (Computer systems)
Human-computer interaction
Computer graphics
Artificial intelligence
Computer engineering
Computer networks
Computer and Information Systems Applications
Computer Vision
User Interfaces and Human Computer Interaction
Computer Graphics
Artificial Intelligence
Computer Engineering and Networks
ISBN 3-030-22514-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 3D Reconstruction and Rendering -- Virtual Reality and Augmented Reality -- Computer Animation -- Geometric Modelling -- Geometric Computing -- Shape and Surface Modelling -- Visual Analytics -- Image Processing -- Pattern Recognition -- Motion Planning -- Gait and Activity Biometric Recognition -- Machine Learning for Graphics and Applications in Security -- Smart Electronics -- Autonomous Navigation Systems -- Robotics -- Geographical Information Systems -- Medicine and Art.
Record Nr. UNINA-9910337842903321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Computer vision - ACCV 2020 : 15th Asian conference on computer vision, Kyoto, Japan, November 30 - December 4, 2020 : revised selected papers, Part 1 / / Hiroshi Ishikawa [and three others], editors
Computer vision - ACCV 2020 : 15th Asian conference on computer vision, Kyoto, Japan, November 30 - December 4, 2020 : revised selected papers, Part 1 / / Hiroshi Ishikawa [and three others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (755 pages) : illustrations
Disciplina 006.37
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
Optical data processing
Artificial intelligence
ISBN 3-030-69525-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- 3D Computer Vision -- Weakly-Supervised Reconstruction of 3D Objects with Large Shape Variation from Single In-the-Wild Images -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Overview -- 3.2 Inference with Multi-scale Features -- 3.3 Shape-Sensitive Geometric Constraints -- 3.4 Training Data Augmentation via Background Manipulation -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Datasets and Protocols -- 4.3 Model Analysis -- 4.4 Ablation Study -- 4.5 Comparison to State-of-the-Arts -- 5 Conclusion -- References -- HPGCNN: Hierarchical Parallel Group Convolutional Neural Networks for Point Clouds Processing -- 1 Introduction -- 2 Related Work -- 3 Hierarchical Parallel Group Convolutional Neural Network -- 3.1 Hierarchical Parallel Group Convolution -- 3.2 Hierarchical Parallel Group Convolutional Neural Network -- 4 Experiments -- 4.1 Shape Recognition -- 4.2 Semantic Segmentation -- 5 Conclusion -- References -- 3D Object Detection and Pose Estimation of Unseen Objects in Color Images with Local Surface Embeddings -- 1 Introduction -- 2 Related Work -- 2.1 3D Object Detection and Pose Estimation from Color Images -- 2.2 Training on Synthetic Images for 6D Pose Estimation -- 2.3 6D Pose Estimation Without Retraining -- 3 Method -- 3.1 Local Surface Embeddings -- 3.2 Predicting the Local Surface Embeddings for New Images -- 3.3 Pose Estimation Algorithm -- 4 Evaluation -- 4.1 Dataset -- 4.2 LSE Prediction Network Architecture and Training -- 4.3 Metrics -- 4.4 Results -- 4.5 Robustness to Texture -- 5 Conclusion -- References -- Reconstructing Creative Lego Models -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Triangle Mesh Generation -- 3.2 Flat Surface Extraction -- 3.3 Colour Information Extraction -- 3.4 Rotational Group Detection -- 3.5 Cuboid Detection.
3.6 Chiselling -- 3.7 Snapping -- 4 Evaluation and Results -- 4.1 Angular DBSCAN -- 4.2 Lego Reconstruction -- 5 Conclusion -- References -- Multi-view Consistency Loss for Improved Single-Image 3D Reconstruction of Clothed People -- 1 Introduction -- 2 Related Work -- 2.1 Single View 3D Human Reconstruction -- 2.2 Datasets for 3D Human Reconstruction -- 3 Single-View Human Shape with Multi-view Training -- 3.1 Learning Architecture -- 3.2 3D Human Representation -- 3.3 The Proposed Loss Functions -- 3.4 3DVH Dataset -- 4 Experimental Evaluation -- 4.1 Implementation Details -- 4.2 Comparison -- 4.3 Generalization to Real Images of People -- 4.4 Ablation Study -- References -- Learning Global Pose Features in Graph Convolutional Networks for 3D Human Pose Estimation -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Revisit GCN -- 3.2 Learning Global Pose Features -- 3.3 Network Architecture -- 4 Experiments -- 4.1 Datasets and Evaluation Protocols -- 4.2 Ablation Study -- 4.3 Comparison with the State of the Art -- 5 Conclusion -- References -- SGNet: Semantics Guided Deep Stereo Matching -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Architecture Overview -- 3.2 Semantic Branch -- 3.3 Residual Module -- 3.4 Confidence Module -- 3.5 Loss Module -- 4 Experiments and Analysis -- 4.1 Ablation Studies -- 4.2 Comparing with Other Methods -- 5 Conclusion -- References -- Reconstructing Human Body Mesh from Point Clouds by Adversarial GP Network -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Network Architecture -- 3.2 Local and Global Spatial Consistency -- 3.3 Training Loss -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Evaluation Protocol -- 4.3 Implementation Details -- 4.4 Comparison with Baselines -- 5 Conclusion -- References.
SDP-Net: Scene Flow Based Real-Time Object Detection and Prediction from Sequential 3D Point Clouds -- 1 Introduction -- 2 Related Work -- 2.1 Single-Frame 3D Object Detection -- 2.2 Multi-frame 3D Object Detection -- 2.3 Object Prediction and Tracking -- 3 SDP-Net -- 3.1 Network Structure -- 3.2 Loss Function -- 4 Experiments -- 4.1 Dataset and Implementation Details -- 4.2 Evaluation Results -- 5 Conclusions -- References -- SAUM: Symmetry-Aware Upsampling Module for Consistent Point Cloud Completion -- 1 Introduction -- 2 Related Works -- 3 Two-Branch Network -- 3.1 Encoder-Decoder Network -- 3.2 Symmetry-Aware Upsampling Module (SAUM) -- 4 Experimental Setting -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Evaluation Metrics -- 5 Results -- 6 Conclusion -- References -- Faster Self-adaptive Deep Stereo -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 The Overall Framework -- 3.2 Knowledge Reverse Distillation -- 3.3 The Adapt-or-Hold Mechanism -- 4 Experiment -- 4.1 Implementation Details -- 4.2 Benchmark Comparison -- 4.3 Ablation Study -- 5 Conclusion and Future Work -- References -- AFN: Attentional Feedback Network Based 3D Terrain Super-Resolution -- 1 Introduction -- 2 Related Work -- 2.1 Terrain Modeling -- 2.2 Super-Resolution of Images -- 2.3 DEM Super-Resolution with Neural Networks -- 3 Method -- 3.1 Proposed Attentional Feedback Network Architecture -- 4 Experimental Setup -- 4.1 Datasets -- 4.2 Implementation Details -- 5 Results and Discussions -- 5.1 Ablation Studies -- 6 Conclusion -- References -- Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point Clouds -- 1 Introduction -- 2 Related Works -- 3 Motivation -- 4 Methodology and Implementation -- 4.1 Methodology -- 4.2 Implementation -- 5 Experiments -- 5.1 Experiments Setting -- 5.2 S3DIS Results -- 5.3 PartNet Results.
5.4 ScanNetV2 Results -- 6 Discussion -- 6.1 Ablation Study -- 6.2 Mechanism Study -- 6.3 Efficiency Study -- 7 Conclusion -- References -- Anatomy and Geometry Constrained One-Stage Framework for 3D Human Pose Estimation -- 1 Introduction -- 2 Related Work -- 2.1 One Stage Methods -- 2.2 Two Stage Methods -- 3 Method -- 3.1 Kinematic Computation -- 3.2 Kinematic Structure Model -- 3.3 Bone-Length and Bone-Symmetry Loss -- 3.4 Multi-view Consistency Constraints -- 3.5 Loss Function -- 4 Experiment -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Experiment Results on Human3.6M Dataset -- 4.4 Experiment Results on MPI-INF-3DHP Dataset -- 4.5 Qualitative Results on MPII Dataset -- 5 Conclusion -- References -- DeepVoxels++: Enhancing the Fidelity of Novel View Synthesis from 3D Voxel Embeddings -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 View-Dependent Patch Feature Extraction -- 3.2 Recurrent-Concurrent Voxel Feature Aggregation -- 3.3 View-Dependent Patch Rendering -- 3.4 Implementation Details -- 4 Experiments and Discussion -- 4.1 Dataset and Metrics -- 4.2 Evaluating 360 Novel View Synthesis -- 4.3 Ablation Studies -- 5 Conclusion and Limitations -- References -- Dehazing Cost Volume for Deep Multi-view Stereo in Scattering Media -- 1 Introduction -- 2 Related Work -- 2.1 Multi-view Stereo -- 2.2 Dehazing -- 2.3 3D Reconstruction in Scattering Media -- 3 Multi-view Stereo in Scattering Media -- 3.1 Image Formation Model -- 3.2 Overview -- 3.3 Dehazing Cost Volume -- 3.4 Network Architecture and Loss Function -- 4 Experiments -- 4.1 Dataset -- 4.2 Training Details -- 4.3 Results -- 4.4 Experiments with Actual Data -- 4.5 Discusssion on Errors of Scattering Parameters -- 5 Conclusion -- References -- Homography-Based Egomotion Estimation Using Gravity and SIFT Features -- 1 Introduction -- 2 Background -- 2.1 DOF Analysis.
2.2 Orientation- and Scale-Covariant Feature Constraints -- 3 Pose Estimation -- 3.1 Points on a Horizontal Plane -- 3.2 Points on a Vertical Plane -- 4 Experiments -- 4.1 Computational Complexity -- 4.2 Synthetic Evaluation -- 4.3 Camera Mounted to a Moving Vehicle -- 4.4 Smart Phone Images -- 5 Conclusions -- References -- Mapping of Sparse 3D Data Using Alternating Projection -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 Alternating Projection (AP) -- 5 Implementation Details -- 5.1 Pre-processing -- 5.2 Full Meta-algorithm with RANSAC -- 6 Experiments -- 6.1 Sensitivity Analysis -- 7 Discussion -- References -- Best Buddies Registration for Point Clouds -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Experiments -- 4.1 Performance Evaluation Setup -- 4.2 Comparing Accuracy and Robustness Between BBR Variants -- 4.3 Accuracy -- 4.4 Robustness -- 4.5 Odometry -- 5 Conclusions -- References -- Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Data -- 1 Introduction -- 2 Related Work -- 2.1 Unimodal Approaches -- 2.2 Depth Completion from RGB and LiDAR -- 3 Method -- 3.1 Data Generation via Projections -- 3.2 RGB Adaptation -- 3.3 Filtering Projection Artifacts for Supervision -- 3.4 Summary of Losses -- 4 Experiments -- 4.1 Ablation Study -- 4.2 Method Evaluation -- 5 Conclusions -- References -- Dynamic Depth Fusion and Transformation for Monocular 3D Object Detection -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Approach Overview -- 3.2 Adaptive Depth-Guided Instance Normalization -- 3.3 Dynamic Depth Transformation -- 3.4 3D Bounding Box Estimation -- 3.5 Feature Extraction -- 3.6 Implementation Details -- 4 Experiments -- 4.1 Results on KITTI -- 4.2 Ablation Study -- 5 Conclusion -- References.
Attention-Aware Feature Aggregation for Real-Time Stereo Matching on Edge Devices.
Record Nr. UNISA-996464413903316
Cham, Switzerland : , : Springer, , [2021]
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Computer Vision – ACCV 2020 [[electronic resource] ] : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part V / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Computer Vision – ACCV 2020 [[electronic resource] ] : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part V / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (XVIII, 706 p. 5 illus., 1 illus. in color.)
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Computer vision
Artificial intelligence
Computer engineering
Computer networks
Pattern recognition systems
Application software
Computer Vision
Artificial Intelligence
Computer Engineering and Networks
Automated Pattern Recognition
Computer and Information Systems Applications
ISBN 3-030-69541-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Face, Pose, Action, and Gesture -- Video-Based Crowd Counting Using a Multi-Scale Optical Flow Pyramid Network -- RealSmileNet: A Deep End-To-End Network for Spontaneous and Posed Smile Recognition -- Decoupled Spatial-Temporal Attention Network for Skeleton-Based Action-Gesture Recognition -- Unpaired Multimodal Facial Expression Recognition -- Gaussian Vector: An Efficient Solution for Facial Landmark Detection -- A Global to Local Double Embedding Method for Multi-person Pose Estimation -- Semi-supervised Facial Action Unit Intensity Estimation with Contrastive Learning -- MMD based Discriminative Learning for Face Forgery Detection -- RE-Net: A Relation Embedded Deep Model for AU Occurrence and Intensity Estimation -- Learning 3D Face Reconstruction with a Pose Guidance Network -- Self-Supervised Multi-View Synchronization Learning for 3D Pose Estimation -- Faster, Better and More Detailed: 3D Face Reconstruction with Graph Convolutional Networks -- Localin Reshuffle Net: Toward Naturally and Efficiently Facial Image Blending -- Rotation Axis Focused Attention Network (RAFA-Net) for Estimating Head Pose -- Unified Application of Style Transfer for Face Swapping and Reenactment -- Multiple Exemplars-based Hallucination for Face Super-resolution and Editing -- Imbalance Robust Softmax for Deep Embedding Learning -- Domain Adaptation Gaze Estimation by Embedding with Prediction Consistency -- Speech2Video Synthesis with 3D Skeleton Regularization and Expressive Body Poses -- 3D Human Motion Estimation via Motion Compression and Refinement -- Spatial Temporal Attention Graph Convolutional Networks with Mechanics-Stream for Skeleton-based Action Recognition -- DiscFace: Minimum Discrepancy Learning for Deep Face Recognition -- Uncertainty Estimation and Sample Selection for Crowd Counting -- Multi-Task Learning for Simultaneous Video Generation and Remote Photoplethysmography Estimation -- Video Analysis and Event Recognition -- Interpreting Video Features: A Comparison of 3D Convolutional Networks and Convolutional LSTM Networks -- Encode the Unseen: Predictive Video Hashing for Scalable Mid-Stream Retrieval -- Active Learning for Video Description With Cluster-Regularized Ensemble Ranking -- Condensed Movies: Story Based Retrieval with Contextual Embeddings -- Play Fair: Frame Contributions in Video Models -- Transforming Multi-Concept Attention into Video Summarization -- Learning to Adapt to Unseen Abnormal Activities under Weak Supervision -- TSI: Temporal Scale Invariant Network for Action Proposal Generation -- Discovering Multi-Label Actor-Action Association in a Weakly Supervised Setting -- Reweighted Non-convex Non-smooth Rank Minimization based Spectral Clustering on Grassmann Manifold -- Biomedical Image Analysis -- Descriptor-Free Multi-View Region Matching for Instance-Wise 3D Reconstruction -- Hierarchical X-Ray Report Generation via Pathology tags and Multi Head Attention -- Self-Guided Multiple Instance Learning for Weakly Supervised Thoracic Disease Classification and Localizationin Chest Radiographs -- MBNet: A Multi-Task Deep Neural Network for Semantic Segmentation and Lumbar Vertebra Inspection on X-ray Images -- Attention-Based Fine-Grained Classification of Bone Marrow Cells -- Learning Multi-Instance Sub-pixel Point Localization -- Utilizing Transfer Learning and a Customized Loss Function for Optic Disc Segmentation from Retinal Images.
Record Nr. UNISA-996464410903316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
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Computer Vision – ACCV 2020 [[electronic resource] ] : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part VI / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Computer Vision – ACCV 2020 [[electronic resource] ] : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part VI / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (XVIII, 705 p. 262 illus., 252 illus. in color.)
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Computer vision
Computer engineering
Computer networks
Artificial intelligence
Pattern recognition systems
Application software
Computer Vision
Computer Engineering and Networks
Artificial Intelligence
Automated Pattern Recognition
Computer and Information Systems Applications
ISBN 3-030-69544-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Applications of Computer Vision, Vision for X -- Query by Strings and Return Ranking Word Regions with Only One Look -- Single-Image Camera Response Function Using Prediction Consistency and Gradual Refinement -- FootNet: An efficient convolutional network for multiview 3D foot reconstruction -- Synthetic-to-real domain adaptation for lane detection -- RAF-AU Database: In-the-Wild Facial Expressions with Subjective Emotion Judgement and Objective AU Annotations -- DoFNet: Depth of Field Difference Learning for Detecting Image Forgery -- Explaining image classifiers by removing input features using generative models -- Do We Need Sound for Sound Source Localization? -- Modular Graph Attention Network for Complex Visual Relational Reasoning -- CloTH-VTON: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON -- Multi-label X-ray Imagery Classification via Bottom-up Attention and Meta Fusion -- Learning End-to-End Action Interaction by Paired-Embedding Data Augmentation -- Sketch-to-Art: Synthesizing Stylized Art Images From Sketches -- Road Obstacle Detection Method Based on an Autoencoder with Semantic Segmentation -- SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection -- Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion -- Audiovisual Transformer with Instance Attention for Audio-Visual Event Localization -- Watch, read and lookup: learning to spot signs from multiple supervisors -- Domain-transferred Face Augmentation Network -- Pose Correction Algorithm for Relative Frames between Keyframes in SLAM -- Dense-Scale Feature Learning in Person Re-Identification -- Class-incremental Learning with Rectified Feature-Graph Preservation -- Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation -- Towards Robust Fine-grained Recognition by Maximal Separation of Discriminative Features -- Visually Guided Sound Source Separation using Cascaded Opponent Filter Network -- Channel Recurrent Attention Networks for Video Pedestrian Retrieval -- In Defense of LSTMs for Addressing Multiple Instance Learning Problems -- Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score -- Show, Conceive and Tell: Image Captioning with Prospective Linguistic Information -- Datasets and Performance Analysis -- RGB-T Crowd Counting from Drone: A Benchmark and MMCCN Network -- Webly Supervised Semantic Embeddings for Large Scale Zero-Shot Learning -- Compensating for the Lack of Extra Training Data by Learning Extra Representation -- Class-Wise Difficulty-Balanced Loss for Solving Class-Imbalance -- OpenTraj: Assessing Prediction Complexity in Human Trajectories Datasets -- Pre-training without Natural Images -- TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines -- A Day on Campus - An Anomaly Detection Dataset for Events in a Single Camera -- A Benchmark and Baseline for Language-Driven Image Editing -- Self-supervised Learning of Orc-Bert Augmentator for Recognizing Few-Shot Oracle Characters -- Understanding Motion in Sign Language: A New Structured Translation Dataset -- FreezeNet: Full Performance by Reduced Storage Costs.
Record Nr. UNISA-996464411703316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
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Computer Vision – ACCV 2020 [[electronic resource] ] : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part IV / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Computer Vision – ACCV 2020 [[electronic resource] ] : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part IV / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (XVIII, 715 p. 284 illus., 278 illus. in color.)
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Computer vision
Artificial intelligence
Computer engineering
Computer networks
Pattern recognition systems
Application software
Computer Vision
Artificial Intelligence
Computer Engineering and Networks
Automated Pattern Recognition
Computer and Information Systems Applications
ISBN 3-030-69538-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Deep Learning for Computer Vision -- In-sample Contrastive Learning and Consistent Attention for Weakly Supervised Object Localization -- Exploiting Transferable Knowledge for Fairness-aware Image Classification -- Introspective Learning by Distilling Knowledge from Online Self-explanation -- Hyperparameter-Free Out-of-Distribution Detection Using Cosine Similarity -- Meta-Learning with Context-Agnostic Initialisations -- Second Order enhanced Multi-glimpse Attention in Visual Question Answering -- Localize to Classify and Classify to Localize: Mutual Guidance in Object Detection -- Unified Density-Aware Image Dehazing and Object Detection in Real-World Hazy Scenes -- Part-aware Attention Network for Person Re-Identification -- Image Captioning through Image Transformer -- Feature Variance Ratio-Guided Channel Pruning for Deep Convolutional Network Acceleration -- Learn more, forget less: Cues from human brain -- Knowledge Transfer Graph for Deep Collaborative Learning -- Regularizing Meta-Learning via Gradient Dropout -- Vax-a-Net: Training-time Defence Against Adversarial Patch Attacks -- Towards Optimal Filter Pruning with Balanced Performance and Pruning Speed -- Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation -- Double Targeted Universal Adversarial Perturbations -- Adversarially Robust Deep Image Super-Resolution using Entropy Regularization -- Online Knowledge Distillation via Multi-branch Diversity Enhancement -- Rotation Equivariant Orientation Estimation for Omnidirectional Localization -- Contextual Semantic Interpretability -- Few-Shot Object Detection by Second-order Pooling -- Depth-Adapted CNN for RGB-D cameras -- Generative Models for Computer Vision -- Over-exposure Correction via Exposure and Scene Information Disentanglement -- Novel-View Human Action Synthesis -- Augmentation Network for Generalised Zero-Shot Learning -- Local Facial Makeup Transfer via Disentangled Representation -- OpenGAN: Open Set Generative Adversarial Networks -- CPTNet: Cascade Pose Transform Network for Single Image Talking Head Animation -- TinyGAN: Distilling BigGAN for Conditional Image Generation -- A cost-effective method for improving and re-purposing large, pre-trained GANs by fine-tuning their class-embeddings -- RF-GAN: A Light and Reconfigurable Network for Unpaired Image-to-Image Translation -- GAN-based Noise Model for Denoising Real Images -- Emotional Landscape Image Generation Using Generative Adversarial Networks -- Feedback Recurrent Autoencoder for Video Compression -- MatchGAN: A Self-Supervised Semi-Supervised Conditional Generative Adversarial Network -- DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution -- dpVAEs: Fixing Sample Generation for Regularized VAEs -- MagGAN: High-Resolution Face Attribute Editing with Mask-Guided Generative Adversarial Network -- EvolGAN: Evolutionary Generative Adversarial Networks -- Sequential View Synthesis with Transformer.
Record Nr. UNISA-996464413403316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
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Lo trovi qui: Univ. di Salerno
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Computer Vision – ACCV 2020 [[electronic resource] ] : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part III / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Computer Vision – ACCV 2020 [[electronic resource] ] : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part III / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (XVIII, 757 p. 245 illus., 229 illus. in color.)
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Computer vision
Artificial intelligence
Computer engineering
Computer networks
Pattern recognition systems
Computer Vision
Artificial Intelligence
Computer Engineering and Networks
Automated Pattern Recognition
ISBN 3-030-69535-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Recognition and Detection -- End-to-end Model-based Gait Recognition -- Horizontal Flipping Assisted Disentangled Feature Learning for Semi-Supervised Person Re-Identification -- MIX'EM: Unsupervised Image Classification using a Mixture of Embeddings -- Backbone Based Feature Enhancement for Object Detection -- Long-Term Cloth-Changing Person Re-identification -- Any-Shot Object Detection -- Background Learnable Cascade for Zero-Shot Object Detection -- Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation -- COG: COnsistent data auGmentation for object perception -- Synthesizing the Unseen for Zero-shot Object Detection -- Fully Supervised and Guided Distillation for One-Stage Detectors -- Visualizing Color-wise Saliency of Black-Box Image Classification Models -- ERIC: Extracting Relations Inferred from Convolutions -- D2D: Keypoint Extraction with Describe to Detect Approach -- Accurate Arbitrary-Shaped Scene Text Detection via Iterative Polynomial Parameter Regression -- Adaptive Spotting: Deep Reinforcement Object Search in 3D Point Clouds -- Efficient Large-Scale Semantic Visual Localization in 2D Maps -- Synthetic-to-Real Unsupervised Domain Adaptation for Scene Text Detection in the Wild -- Scale-Aware Polar Representation for Arbitrarily-Shaped Text Detection -- Branch Interaction Network for Person Re-identification -- BLT: Balancing Long-Tailed Datasets with Adversarially-Perturbed Images -- Jointly Discriminating and Frequent Visual Representation Mining -- Discrete Spatial Importance-Based Deep Weighted Hashing -- Low-level Sensor Fusion Network for 3D Vehicle Detection using Radar Range-Azimuth Heatmap and Monocular Image -- MLIFeat: Multi-level information fusion based deep local features -- CLASS: Cross-Level Attention and Supervision for Salient Objects Detection -- Cascaded Transposed Long-range Convolutions for Monocular Depth Estimation -- Optimization, Statistical Methods, and Learning -- Bridging Adversarial and Statistical Domain Transfer via Spectral Adaptation Networks -- Large-Scale Cross-Domain Few-Shot Learning -- Channel Pruning for Accelerating Convolutional Neural Networks via Wasserstein Metric -- Progressive Batching for Efficient Non-linear Least Squares -- Fast and Differentiable Message Passing on Pairwise Markov Random Fields -- A Calibration Method for the Generalized Imaging Model with Uncertain Calibration Target Coordinates -- Graph-based Heuristic Search for Module Selection Procedure in Neural Module Network -- Towards Fast and Robust Adversarial Training for Image Classification -- Few-Shot Zero-Shot Learning: Knowledge Transfer with Less Supervision -- Lossless Image Compression Using a Multi-Scale Progressive Statistical Model -- Spatial Class Distribution Shift in Unsupervised Domain Adaptation: Local Alignment Comes to Rescue -- Robot Vision -- Point Proposal based Instance Segmentation with Rectangular Masks for Robot Picking Task -- Multi-task Learning with Future States for Vision-based Autonomous Driving -- MTNAS: Search Multi-Task Networks for Autonomous Driving -- Compact and Fast Underwater Segmentation Network for Autonomous Underwater Vehicles -- L2R GAN: LiDAR-to-Radar Translation -- V2A - Vision to Action: Learning robotic arm actions based on vision and language -- To Filter Prune, or to Layer Prune, That Is The Question.
Record Nr. UNISA-996464412203316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
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Computer Vision – ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part I / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Computer Vision – ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part I / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (755 pages) : illustrations
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Computer vision
Artificial intelligence
Computer engineering
Computer networks
Pattern recognition systems
Computer Vision
Artificial Intelligence
Computer Engineering and Networks
Computer Communication Networks
Automated Pattern Recognition
ISBN 3-030-69525-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 3D Computer Vision -- Weakly-supervised Reconstruction of 3D Objects with Large Shape Variation from Single In-the-Wild Images -- HPGCNN: Hierarchical Parallel Group Convolutional Neural Networks for Point Clouds Processing -- 3D Object Detection and Pose Estimation of Unseen Objects in Color Images with Local Surface Embeddings -- Reconstructing Creative Lego Models, George Tattersall -- Multi-View Consistency Loss for Improved Single-Image 3D Reconstruction of Clothed People -- Learning Global Pose Features in Graph Convolutional Networks for 3D Human Pose Estimation -- SGNet: Semantics Guided Deep Stereo Matching -- Reconstructing Human Body Mesh from Point Clouds by Adversarial GP Network -- SDP-Net: Scene Flow Based Real-time Object Detection and Prediction from Sequential 3D Point Clouds -- SAUM: Symmetry-Aware Upsampling Module for Consistent Point Cloud Completion -- Faster Self-adaptive Deep Stereo -- AFN: Attentional Feedback Network based 3D Terrain Super-Resolution -- Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point Clouds -- Anatomy and Geometry Constrained One-Stage Framework for 3D Human Pose Estimation -- DeepVoxels++: Enhancing the Fidelity of Novel View Synthesis from 3D Voxel Embeddings -- Dehazing Cost Volume for Deep Multi-view Stereo in Scattering Media -- Homography-based Egomotion Estimation Using Gravity and SIFT Features -- Mapping of Sparse 3D Data using Alternating Projection -- Best Buddies Registration for Point Clouds -- Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Data -- Dynamic Depth Fusion and Transformation for Monocular 3D Object Detection -- Attention-Aware Feature Aggregation for Real-time Stereo Matching on Edge Devices -- FKAConv: Feature-Kernel Alignment for Point Cloud Convolution -- Sparse Convolutions on Continuous Domains for Point Cloud and Event Stream Networks -- IAFA: Instance-Aware Feature Aggregation for 3D Object Detection from a Single Image -- Attended-Auxiliary Supervision Representation for Face Anti-spoofing -- 3D Object Detection from Consecutive Monocular Images -- Data-Efficient Ranking Distillation for Image Retrieval -- Quantum Robust Fitting -- HDD-Net: Hybrid Detector Descriptor with Mutual Interactive Learning -- Segmentation and Grouping -- RGB-D Co-attention Network for Semantic Segmentation -- Semantics through Time: Semi-supervised Segmentation of Aerial Videos with Iterative Label Propagation -- Dense Dual-Path Network for Real-time Semantic Segmentation -- Learning More Accurate Features for Semantic Segmentation in CycleNet -- 3D Guided Weakly Supervised Semantic Segmentation -- Real-Time Segmentation Networks should be Latency Aware -- Mask-Ranking Network for Semi-Supervised Video Object Segmentation -- SDCNet: Size Divide and Conquer Network for Salient Object Detection -- Bidirectional Pyramid Networks for Semantic Segmentation -- DEAL: Difficulty-aware Active Learning for Semantic Segmentation -- EPSNet: Efficient Panoptic Segmentation Network with Cross-layer Attention Fusion -- Local Context Attention for Salient Object Segmentation -- Generic Image Segmentation in Fully Convolutional Networks by Superpixel Merging Map.
Record Nr. UNINA-9910483298103321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Computer Vision – ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part II / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Computer Vision – ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part II / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (733 pages)
Disciplina 006.3
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Computer vision
Artificial intelligence
Pattern recognition systems
Computer engineering
Computer networks
Computer Vision
Artificial Intelligence
Automated Pattern Recognition
Computer Engineering and Networks
ISBN 3-030-69532-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Low-Level Vision, Image Processing -- Image Inpainting with Onion Convolutions -- Accurate and Efficient Single Image Super-Resolution with Matrix Channel Attention Network -- Second-order Camera-aware Color Transformation for Cross-domain Person Re-identification -- CS-MCNet:A Video Compressive Sensing Reconstruction Network with Interpretable Motion Compensation -- MCGKT-Net: Multi-level Context Gating Knowledge Transfer Network for Single Image Deraining -- Degradation Model Learning for Real-World Single Image Super-resolution -- Chromatic Aberration Correction Using Cross-Channel Prior in Shearlet Domain -- Raw-Guided Enhancing Reprocess of Low-Light Image via Deep Exposure Adjustment -- Robust High Dynamic Range (HDR) Imaging with Complex Motion and Parallax -- Low-light Color Imaging via Dual Camera Acquisition -- Frequency Attention Network: Blind Noise Removal for Real Images -- Restoring Spatially-Heterogeneous Distortions using Mixture of Experts Network -- Color Enhancement usingGlobal Parameters and Local Features Learning -- An Efficient Group Feature Fusion Residual Network for Image Super-Resolution -- Adversarial Image Composition with Auxiliary Illumination -- Overwater Image Dehazing via Cycle-Consistent Generative Adversarial Network -- Lightweight Single-Image Super-Resolution Network with Attentive Auxiliary Feature Learning -- Multi-scale Attentive Residual Dense Network for Single Image Rain Removal -- FAN: Feature Adaptation Network for Surveillance Face Recognition and Normalization -- Human Motion Deblurring using Localized Body Prior -- Synergistic Saliency and Depth Prediction for RGB-D Saliency Detection -- Deep Snapshot HDR Imaging Using Multi-Exposure Color Filter Array -- Deep Priors inside an Unrolled and Adaptive Deconvolution Model -- Motion and Tracking -- Adaptive Spatio-Temporal Regularized Correlation Filters for UAV-based Tracking -- Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimation -- Self-supervised Sparse toDense Motion Segmentation -- Recursive Bayesian Filtering for Multiple Human Pose Tracking from Multiple Cameras -- Adversarial Refinement Network for Human Motion Prediction -- Semantic Synthesis of Pedestrian Locomotion -- Betrayed by Motion: Camouflaged Object Discovery via Motion Segmentation -- Visual Tracking by TridentAlign and Context Embedding -- Leveraging Tacit Information Embedded in CNN Layers for Visual Tracking -- A Two-Stage Minimum Cost Multicut Approach to Self-Supervised Multiple Person Tracking -- Learning Local Feature Descriptors for Multiple Object Tracking -- VAN: Versatile Affinity Network for End-to-end Online Multi-Object Tracking -- COMET: Context-Aware IoU-Guided Network for Small Object Tracking -- Adversarial Semi-Supervised Multi-Domain Tracking -- Tracking-by-Trackers with a Distilled and Reinforced Model -- Motion Prediction Using Temporal Inception Module -- A Sparse Gaussian Approach to Region-Based 6DoF Object Tracking -- Modeling Cross-Modal interaction in a Multi-detector, Multi-modal Tracking Framework -- Dense Pixel-wise Micro-motion Estimation of Object Surface by using Low Dimensional Embedding of Laser Speckle Pattern.
Record Nr. UNINA-9910484687903321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Computer Vision – ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part IV / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Computer Vision – ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part IV / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (XVIII, 715 p. 284 illus., 278 illus. in color.)
Disciplina 006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Computer vision
Artificial intelligence
Computer engineering
Computer networks
Pattern recognition systems
Application software
Computer Vision
Artificial Intelligence
Computer Engineering and Networks
Automated Pattern Recognition
Computer and Information Systems Applications
ISBN 3-030-69538-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Deep Learning for Computer Vision -- In-sample Contrastive Learning and Consistent Attention for Weakly Supervised Object Localization -- Exploiting Transferable Knowledge for Fairness-aware Image Classification -- Introspective Learning by Distilling Knowledge from Online Self-explanation -- Hyperparameter-Free Out-of-Distribution Detection Using Cosine Similarity -- Meta-Learning with Context-Agnostic Initialisations -- Second Order enhanced Multi-glimpse Attention in Visual Question Answering -- Localize to Classify and Classify to Localize: Mutual Guidance in Object Detection -- Unified Density-Aware Image Dehazing and Object Detection in Real-World Hazy Scenes -- Part-aware Attention Network for Person Re-Identification -- Image Captioning through Image Transformer -- Feature Variance Ratio-Guided Channel Pruning for Deep Convolutional Network Acceleration -- Learn more, forget less: Cues from human brain -- Knowledge Transfer Graph for Deep Collaborative Learning -- Regularizing Meta-Learning via Gradient Dropout -- Vax-a-Net: Training-time Defence Against Adversarial Patch Attacks -- Towards Optimal Filter Pruning with Balanced Performance and Pruning Speed -- Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation -- Double Targeted Universal Adversarial Perturbations -- Adversarially Robust Deep Image Super-Resolution using Entropy Regularization -- Online Knowledge Distillation via Multi-branch Diversity Enhancement -- Rotation Equivariant Orientation Estimation for Omnidirectional Localization -- Contextual Semantic Interpretability -- Few-Shot Object Detection by Second-order Pooling -- Depth-Adapted CNN for RGB-D cameras -- Generative Models for Computer Vision -- Over-exposure Correction via Exposure and Scene Information Disentanglement -- Novel-View Human Action Synthesis -- Augmentation Network for Generalised Zero-Shot Learning -- Local Facial Makeup Transfer via Disentangled Representation -- OpenGAN: Open Set Generative Adversarial Networks -- CPTNet: Cascade Pose Transform Network for Single Image Talking Head Animation -- TinyGAN: Distilling BigGAN for Conditional Image Generation -- A cost-effective method for improving and re-purposing large, pre-trained GANs by fine-tuning their class-embeddings -- RF-GAN: A Light and Reconfigurable Network for Unpaired Image-to-Image Translation -- GAN-based Noise Model for Denoising Real Images -- Emotional Landscape Image Generation Using Generative Adversarial Networks -- Feedback Recurrent Autoencoder for Video Compression -- MatchGAN: A Self-Supervised Semi-Supervised Conditional Generative Adversarial Network -- DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution -- dpVAEs: Fixing Sample Generation for Regularized VAEs -- MagGAN: High-Resolution Face Attribute Editing with Mask-Guided Generative Adversarial Network -- EvolGAN: Evolutionary Generative Adversarial Networks -- Sequential View Synthesis with Transformer.
Record Nr. UNINA-9910484687303321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Materiale a stampa
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