| TÃtulo : |
15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part V |
| Tipo de documento: |
documento electrónico |
| Autores: |
Ishikawa, Hiroshi, ; Liu, Cheng-Lin, ; Pajdla, Tomas, ; Shi, Jianbo, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2021 |
| Número de páginas: |
XVIII, 706 p. 5 ilustraciones, 1 ilustraciones en color. |
| ISBN/ISSN/DL: |
978-3-030-69541-5 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Palabras clave: |
Visión por computador Inteligencia artificial IngenierÃa Informática Red de computadoras Sistemas de reconocimiento de patrones Software de la aplicacion IngenierÃa Informática y Redes Reconocimiento de patrones automatizado Aplicaciones informáticas y de sistemas de información |
| Ãndice Dewey: |
006.37 Visión artificial |
| Resumen: |
El conjunto de seis volúmenes de LNCS 12622-12627 constituye las actas de la 15.ª Conferencia asiática sobre visión artificial, ACCV 2020, celebrada en Kioto (Japón) en noviembre/diciembre de 2020.* El total de 254 contribuciones se revisó cuidadosamente y se seleccionó de 768 presentaciones durante dos rondas de revisión y mejora. Los artÃculos se centran en los siguientes temas: Parte I: visión artificial en 3D; segmentación y agrupamiento Parte II: visión de bajo nivel, procesamiento de imágenes; movimiento y seguimiento Parte III: reconocimiento y detección; optimización, métodos estadÃsticos y aprendizaje; visión robótica Parte IV: aprendizaje profundo para visión artificial, modelos generativos para visión artificial Parte V: rostro, pose, acción y gesto; análisis de vÃdeo y reconocimiento de eventos; análisis de imágenes biomédicas Parte VI: aplicaciones de la visión artificial; visión para X; conjuntos de datos y análisis de rendimiento *La conferencia se celebró de forma virtual. |
| Nota de contenido: |
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. |
| En lÃnea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part V [documento electrónico] / Ishikawa, Hiroshi, ; Liu, Cheng-Lin, ; Pajdla, Tomas, ; Shi, Jianbo, . - 1 ed. . - [s.l.] : Springer, 2021 . - XVIII, 706 p. 5 ilustraciones, 1 ilustraciones en color. ISBN : 978-3-030-69541-5 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
| Palabras clave: |
Visión por computador Inteligencia artificial IngenierÃa Informática Red de computadoras Sistemas de reconocimiento de patrones Software de la aplicacion IngenierÃa Informática y Redes Reconocimiento de patrones automatizado Aplicaciones informáticas y de sistemas de información |
| Ãndice Dewey: |
006.37 Visión artificial |
| Resumen: |
El conjunto de seis volúmenes de LNCS 12622-12627 constituye las actas de la 15.ª Conferencia asiática sobre visión artificial, ACCV 2020, celebrada en Kioto (Japón) en noviembre/diciembre de 2020.* El total de 254 contribuciones se revisó cuidadosamente y se seleccionó de 768 presentaciones durante dos rondas de revisión y mejora. Los artÃculos se centran en los siguientes temas: Parte I: visión artificial en 3D; segmentación y agrupamiento Parte II: visión de bajo nivel, procesamiento de imágenes; movimiento y seguimiento Parte III: reconocimiento y detección; optimización, métodos estadÃsticos y aprendizaje; visión robótica Parte IV: aprendizaje profundo para visión artificial, modelos generativos para visión artificial Parte V: rostro, pose, acción y gesto; análisis de vÃdeo y reconocimiento de eventos; análisis de imágenes biomédicas Parte VI: aplicaciones de la visión artificial; visión para X; conjuntos de datos y análisis de rendimiento *La conferencia se celebró de forma virtual. |
| Nota de contenido: |
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. |
| En lÃnea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
|  |
15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part V
