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001434649 020__ $$a9783030695415$$q(electronic bk.)
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001434649 0247_ $$a10.1007/978-3-030-69541-5$$2doi
001434649 035__ $$aSP(OCoLC)1241066146
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001434649 049__ $$aISEA
001434649 050_4 $$aTA1634
001434649 08204 $$a006.3/7$$223
001434649 1112_ $$aAsian Conference on Computer Vision$$n(15th :$$d2020 :$$cOnline)
001434649 24510 $$aComputer vision - ACCV 2020 :$$b15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020 : revised selected papers.$$nPart V /$$cHiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi (eds.).
001434649 24630 $$aACCV 2020
001434649 264_1 $$aCham :$$bSpringer,$$c[2021]
001434649 300__ $$a1 online resource (xviii, 706 pages) :$$billustrations
001434649 336__ $$atext$$btxt$$2rdacontent
001434649 337__ $$acomputer$$bc$$2rdamedia
001434649 338__ $$aonline resource$$bcr$$2rdacarrier
001434649 347__ $$atext file
001434649 347__ $$bPDF
001434649 4901_ $$aLecture notes in computer science ;$$v12626
001434649 4901_ $$aLNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics
001434649 500__ $$aInternational conference proceedings.
001434649 500__ $$aIncludes author index.
001434649 5050_ $$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.
001434649 506__ $$aAccess limited to authorized users.
001434649 520__ $$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.
001434649 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed March 23, 2021).
001434649 650_0 $$aComputer vision$$vCongresses.
001434649 650_0 $$aOptical data processing.
001434649 650_0 $$aArtificial intelligence.
001434649 650_0 $$aComputers.
001434649 650_0 $$aPattern perception.
001434649 650_0 $$aApplication software.
001434649 650_6 $$aVision par ordinateur$$vCongrès.
001434649 650_6 $$aTraitement optique de l'information.
001434649 650_6 $$aIntelligence artificielle.
001434649 650_6 $$aOrdinateurs.
001434649 650_6 $$aPerception des structures.
001434649 650_6 $$aLogiciels d'application.
001434649 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001434649 655_7 $$aConference papers and proceedings.$$2lcgft
001434649 655_7 $$aActes de congrès.$$2rvmgf
001434649 655_0 $$aElectronic books.
001434649 7001_ $$aIshikawa, Hiroshi,$$eeditor.
001434649 7001_ $$aLiu, Cheng-Lin,$$eeditor.
001434649 7001_ $$aPajdla, Tomáš,$$eeditor.
001434649 7001_ $$aShi, Jianbo,$$eeditor.
001434649 77608 $$iPrint version:$$z9783030695408
001434649 77608 $$iPrint version:$$z9783030695422
001434649 830_0 $$aLecture notes in computer science ;$$v12626.
001434649 830_0 $$aLNCS sublibrary.$$nSL 6,$$pImage processing, computer vision, pattern recognition, and graphics.
001434649 852__ $$bebk
001434649 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-69541-5$$zOnline Access$$91397441.1
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001434649 980__ $$aBIB
001434649 980__ $$aEBOOK
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