Pattern Recognition and Computer Vision : 4th Chinese Conference, PRCV 2021, Beijing, China, October 29 - November 1, 2021, Proceedings, Part I / edited by Huimin Ma, Liang Wang, Changshui Zhang, Fei Wu, Tieniu Tan, Yaonan Wang, Jianhuang Lai, Yao Zhao.

Format:

Book

Contributor:

Ma, Huimin, Editor.

Wang, Liang, Editor.

Zhang, Changshui, Editor.

Wu, Fei, Editor.

Tan, Tieniu, Editor.

Wang, Yaonan, Editor.

Lai, Jianhuang., Editor.

Zhao, Yao, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 13019

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 13019

Language:

English

Subjects (All):

Computer vision.

Computer engineering.

Computer networks.

Computer systems.

Machine learning.

Computer Vision.

Computer Engineering and Networks.

Computer Communication Networks.

Computer System Implementation.

Machine Learning.

Local Subjects:

Computer Vision.

Computer Engineering and Networks.

Computer Communication Networks.

Computer System Implementation.

Machine Learning.

Physical Description:

1 online resource (XIX, 617 pages) : 219 illustrations, 208 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

The 4-volume set LNCS 13019, 13020, 13021 and 13022 constitutes the refereed proceedings of the 4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021, held in Beijing, China, in October-November 2021. The 201 full papers presented were carefully reviewed and selected from 513 submissions. The papers have been organized in the following topical sections: Object Detection, Tracking and Recognition; Computer Vision, Theories and Applications, Multimedia Processing and Analysis; Low-level Vision and Image Processing; Biomedical Image Processing and Analysis; Machine Learning, Neural Network and Deep Learning, and New Advances in Visual Perception and Understanding.

Contents:

Object Detection, Tracking and Recognition

High-performance Discriminative Tracking with Target-aware Feature Embeddings.-3D Multi-Object Detection and Tracking with Sparse Stationary LiDAR

CRNet: Centroid Radiation Network for Temporal Action Localization

Weakly Supervised Temporal Action Localization with Segment-Level Labels

Locality-constrained collaborative representation with multi-resolution dictionary for face recognition

Fast and Fusion: Real-time Pedestrian Detector Boosted by Body-head Fusion

STA-GCN: Spatio-Temporal AU Graph Convolution Network for Facial Micro-Expression Recognition

Attentive Contrast Learning Network for Fine-grained Classification

Relation-Based Knowledge Distillation for Anomaly Detection

High Power-efficient and Performance-density FPGA Accelerator for CNN-based Object Detection

Relation-Guided Actor Attention for Group Activity Recognition

MVAD-Net: Learning View-Aware and Domain-Invariant Representation for Baggage Re-Identification

Joint Attention Mechanism for Unsupervised Video Object Segmentation.-Foreground Feature Selection and Alignment for Adaptive Object Detection

Exploring Category-shared and Category-specific Features for Fine-Grained Image Classification.-Deep Mixture of Adversarial Autoencoders Clustering Network

SA-InterNet: Scale-aware Interaction Network for Joint Crowd Counting and Localization

Conditioners for Adaptive Regression Tracking

Attention Template Update Model for Siamese Tracker

Insight on Attention Modules for Skeleton-Based Action Recognition

AO-AutoTrack: Anti-Occlusion Real-Time UAV Tracking Based on Spatio-temporal Context

Two-stage Recognition Algorithm for Untrimmed Converter Steelmaking Flame Video

Scale-aware Multi-branch Decoder for Salient Object Detection

Dense End Face Detection Network for Counting Bundled Steel Bars Based on Densely End Face Detection Network for Counting Bundled Steel Bars Based on YoloV5

POT: A Dataset of Panoramic Object Tracking

DP-YOLOv5:Computer Vision-Based Risk Behavior Detection in Power Grids.-Distillation-based Multi-Exit Fully Convolutional Network for Visual Tracking.-Handwriting Trajectory Reconstruction using Spatial-Temporal Encoder-Decoder Network

Scene Semantic Guidance for Object Detection

Training Person Re-Identification Networks with Transferred Images

ACFIM: Adaptively Cyclic Feature Information- interaction model for Object Detection

Research of robust video object tracking algorithm based on Jetson Nano embedded platform

Classification-IoU Joint Label Assignment For End-to-End Object Detection

Joint Learning Appearance and Motion Models for Visual Tracking

ReFlowNet: Revisiting Coarse-to-fine Learning of Optical Flow

Local Mutual Metric Network for Few-Shot Image Classification

SimplePose V2: Greedy Offset-Guided Keypoint Grouping for Human Pose Estimation

Control Variates for Similarity Search

Pyramid Self-Attention for Semantic Segmentation

Re-identify Deformable Targets for Visual Tracking

End-to-End Detection and Recognition of Arithmetic Expressions

FD-Net: A Fully Dilated Convolutional Network for Historical Document Image Binarization

Appearance-Motion Fusion Network for Video Anomaly Detection

Can DNN Detectors Compete against Human Vision in Object Detection Task?

Group Re-Identification Based on single feature attention learning network(SFALN)

Contrastive Cycle Consistency Learning for Unsupervised Visual Tracking

Group-Aware Disentangle Learning for Head Pose Estimation

Facilitating 3D Object Tracking in Point Clouds with Image Semantics and Geometry

Multi-Criteria Confidence Evaluation for Robust Visual Tracking.

Other Format:

Printed edition:

ISBN:

978-3-030-88004-0

9783030880040

Access Restriction:

Restricted for use by site license.