Sharable and individual multi-view metric learning
This paper presents a sharable and individual multi-view metric learning (MvML) approach for visual recognition. Unlike conventional metric leaning methods which learn a distance metric on either a single type of feature representation or a concatenated representation of multiple types of features,...
Main Authors: | Hu, Junlin, Lu, Jiwen, Tan, Yap-Peng |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/139872 |
Similar Items
-
Local large-margin multi-metric learning for face and kinship verification
by: Hu, Junlin, et al.
Published: (2020) -
Deep transfer metric learning
by: Hu, Junlin, et al.
Published: (2016) -
Representation Discovery for Kernel-Based Reinforcement Learning
by: Zewdie, Dawit H., et al.
Published: (2015) -
Multi-label metric transfer learning jointly considering instance space and label space distribution divergence
by: Jiang, Siyu, et al.
Published: (2019) -
Off-feature information incorporated metric learning for face recognition
by: Huang, Renjie, et al.
Published: (2020)