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

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
• Edizione: 1st ed. 2021.
• Descrizione fisica: 1 online resource (XVIII, 706 p. 5 illus., 1 illus. in color.)
• Disciplina: 006.37
• 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
• Persona (resp. second.): IshikawaHiroshi; LiuCheng-Lin; PajdlaTomas; ShiJianbo
• 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.
• Sommario/riassunto: The six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.* The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; segmentation and grouping Part II: low-level vision, image processing; motion and tracking Part III: recognition and detection; optimization, statistical methods, and learning; robot vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis Part VI: applications of computer vision; vision for X; datasets and performance analysis *The conference was held virtually.
• Titolo autorizzato: Computer vision-ACCV 2020
• ISBN: 3-030-69541-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996464410903316
• Lo trovi qui: Univ. di Salerno
• Serie: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 12626