Computer Vision - ACCV 2020 Workshops
15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, Revised Selected Papers
Published on 23. February 2021
VIII, 199 pages
978-3-030-69756-3 (ISBN)
Description
This book constitutes the refereed post-conference proceedings of four workshops held at the 15th Asian Conference on Computer Vision, ACCV 2020, which was held in Kyoto, Japan, in November/ December 2020.*
The 13 papers were carefully reviewed and selected from the following two workshops: Machine Learning and Computing for Visual Semantic Analysis (MLCSA) and Multi-Visual-Modality Human Activity Understanding (MMHAU).
*The conference and workshops were held virtually.
More details
Series
Edition
1st ed. 2021
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Product notice
Reflowable
Illustrations
VIII, 199 p. 79 illus., 68 illus. in color.
File size
40,69 MB
ISBN-13
978-3-030-69756-3 (9783030697563)
DOI
10.1007/978-3-030-69756-3
Schweitzer Classification
Other editions
Additional editions
Imari Sato | Bohyung Han
Computer Vision - ACCV 2020 Workshops
15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, Revised Selected Papers
Book
02/2021
Springer
€53.49
Shipment within 7-9 days
Content
Spatial and Channel Attention Modulated Network for Medical Image Segmentation.- Parallel-Connected Residual Channel Attention Network for Remote Sensing Image Super-Resolution.- Unsupervised Multispectral and Hyperspectral Image Fusion with Deep Spatial and Spectral Priors.- G-GCSN: Global Graph Convolution Shrinkage Network for Emotion Perception from Gait.- Cell Detection and Segmentation in Microscopy Images with Improved Mask R-CNN.- BdSL36: A Dataset for Bangladeshi Sign Letters Recognition.- 3D Semantic Segmentation for Large-Scale Scene Understanding.- A Weakly Supervised Convolutional Network for Change Segmentation and Classification.- Visible and Thermal Camera-based Jaywalking Estimation using a Hierarchical Deep Learning Framework.- Towards Locality Similarity Preserving to 3D Human Pose Estimation.- Iterative Self-distillation for Precise Facial Landmark Localization.- Multiview Similarity Learning for Robust Visual Clustering.- Real-time Spatio-temporal Action Localization via Learning Motion Representation.
