AGUnet: Annotation-guided U-net for fast one-shot video object segmentation

Yingjie Yin; De Xu; Xingang Wang; Lei Zhang

doi:10.1016/j.patcog.2020.107580

ScienceGate Book Chapters

JOURNAL ARTICLE

AGUnet: Annotation-guided U-net for fast one-shot video object segmentation

Yingjie Yin De Xu Xingang Wang Lei Zhang

Year: 2020 Journal: Pattern Recognition Vol: 110 Pages: 107580-107580 Publisher: Elsevier BV

DOI: 10.1016/j.patcog.2020.107580

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Artificial intelligence Segmentation Computer vision Annotation Convolutional neural network Object (grammar) Shot (pellet) Gradient descent Frame (networking) Pattern recognition (psychology) Image segmentation Fuse (electrical) Artificial neural network

Metrics

Cited By

1.78

FWCI (Field Weighted Citation Impact)

Refs

0.86

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Visual Attention and Saliency Detection

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Video Surveillance and Tracking Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

AGUnet: Annotation-guided U-net for fast one-shot video object segmentation

Metrics

Citation History

Topics

Related Documents

Efficient One-Shot Video Object Segmentation

One-Shot Image Segmentation with U-Net

Guided Co-Segmentation Network for Fast Video Object Segmentation

One-Shot Video Object Segmentation Using Attention Transfer

Make One-Shot Video Object Segmentation Efficient Again