소장자료
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020 | ▼a9783030695415▼9978-3-030-69541-5▲ | ||
024 | 7 | ▼a10.1007/978-3-030-69541-5▼2doi▲ | |
050 | 4 | ▼aTA1634▲ | |
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245 | 1 | 0 | ▼aComputer Vision – ACCV 2020▼h[electronic resource] :▼b15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part V /▼cedited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi.▲ |
250 | ▼a1st ed. 2021.▲ | ||
264 | 1 | ▼aCham :▼bSpringer International Publishing :▼bImprint: Springer,▼c2021.▲ | |
300 | ▼aXVIII, 706 p. 5 illus., 1 illus. in color.▼bonline resource.▲ | ||
336 | ▼atext▼btxt▼2rdacontent▲ | ||
337 | ▼acomputer▼bc▼2rdamedia▲ | ||
338 | ▼aonline resource▼bcr▼2rdacarrier▲ | ||
347 | ▼atext file▼bPDF▼2rda▲ | ||
490 | 1 | ▼aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;▼v12626▲ | |
505 | 0 | ▼aFace, 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.▲ | |
520 | ▼aThe 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.▲ | ||
650 | 0 | ▼aComputer vision.▲ | |
650 | 0 | ▼aArtificial intelligence.▲ | |
650 | 0 | ▼aComputer engineering.▲ | |
650 | 0 | ▼aComputer networks .▲ | |
650 | 0 | ▼aPattern recognition systems.▲ | |
650 | 0 | ▼aApplication software.▲ | |
650 | 1 | 4 | ▼aComputer Vision.▲ |
650 | 2 | 4 | ▼aArtificial Intelligence.▲ |
650 | 2 | 4 | ▼aComputer Engineering and Networks.▲ |
650 | 2 | 4 | ▼aAutomated Pattern Recognition.▲ |
650 | 2 | 4 | ▼aComputer and Information Systems Applications.▲ |
700 | 1 | ▼aIshikawa, Hiroshi.▼eeditor.▼4edt▼4http://id.loc.gov/vocabulary/relators/edt▲ | |
700 | 1 | ▼aLiu, Cheng-Lin.▼eeditor.▼4edt▼4http://id.loc.gov/vocabulary/relators/edt▲ | |
700 | 1 | ▼aPajdla, Tomas.▼eeditor.▼4edt▼4http://id.loc.gov/vocabulary/relators/edt▲ | |
700 | 1 | ▼aShi, Jianbo.▼eeditor.▼4edt▼4http://id.loc.gov/vocabulary/relators/edt▲ | |
710 | 2 | ▼aSpringerLink (Online service)▲ | |
773 | 0 | ▼tSpringer Nature eBook▲ | |
776 | 0 | 8 | ▼iPrinted edition:▼z9783030695408▲ |
776 | 0 | 8 | ▼iPrinted edition:▼z9783030695422▲ |
830 | 0 | ▼aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;▼v12626▲ | |
856 | 4 | 0 | ▼uhttps://doi.org/10.1007/978-3-030-69541-5▲ |
Computer Vision – ACCV 2020[electronic resource] : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part V
자료유형
국외eBook
서명/책임사항
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.
판사항
1st ed. 2021.
형태사항
XVIII, 706 p. 5 illus., 1 illus. in color. online resource.
총서사항
내용주기
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.
요약주기
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.
주제
ISBN
9783030695415
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