Computer vision -- ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, revised selected papers
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書誌事項
Computer vision -- ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, revised selected papers
(Lecture notes in computer science, 12626 . LNCS sublibrary ; SL 6 . Image processing,
Springer, c2021
- pt. 5
- タイトル別名
-
ACCV 2020
大学図書館所蔵 全1件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
"The Asian Conference on Computer Vision (ACCV) 2020, originally planned to take place in Kyoto, Japan, was held online during November 30 - December 4, 2020."--Preface
Other editors: Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
Includes bibliographical references and author index
内容説明・目次
内容説明
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.
目次
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.
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