Title
CIMask: Segmenting instances by class-specific semantic feature extraction and instance-specific attribute discrimination
Abstract
•We decompose instance segmentation into class-specific semantic extraction and instance-specific attribute discrimination, the proposed novel method is called CIMask.•To better handle ambiguous samples, a novel center-aware sampling mechanism is introduced for generating ground truth.
Year
DOI
Venue
2021
10.1016/j.neucom.2021.08.033
Neurocomputing
Keywords
DocType
Volume
Instance segmentation,Semantic-specific,Instance-specific,Center-aware sampling
Journal
464
ISSN
Citations 
PageRank 
0925-2312
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Canqun Xiang111.36
Wenbin Zou226819.75
Chen Xu326929.36