Computer Vision ¿ ACCV 2020 Workshops

15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 ¿ December 4, 2020, Revised Selected Papers
Herausgegeben:Sato, Imari; Han, Bohyung

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Lecture Notes in Computer Science 12628
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-69755-6
• 1st ed. 2021
• Seitenzahl: 208
• Erscheinungstermin: 24. Februar 2021
• Englisch
• Abmessung: 235mm x 155mm x 12mm
• Gewicht: 324g
• ISBN-13: 9783030697556
• ISBN-10: 303069755X
• Artikelnr.: 60950399

Inhaltsangabe

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.