Deep robust multilevel semantic hashing for multi-label cross-modal retrieval
Hashing based cross-modal retrieval has recently made significant progress. But straightforward embedding data from different modalities involving rich semantics into a joint Hamming space will inevitably produce false codes due to the intrinsic modality discrepancy and noises. We present a novel d...
Saved in:
Main Authors: | Song, Ge, Tan, Xiaoyang, Zhao, Jun, Yang, Ming |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/164098 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Learning robust multi-label hashing for efficient image retrieval
by: CHEN, Haibao, et al.
Published: (2016) -
Learning reconfigurable hashing for diverse semantics
by: Mu, Y., et al.
Published: (2013) -
Online cross-modal hashing for web image retrieval
by: XIE, Liang, et al.
Published: (2016) -
Learning a cross-modal hashing network for multimedia search
by: Tan, Yap Peng, et al.
Published: (2018) -
Unsupervised multi-graph cross-modal hashing for large-scale multimedia retrieval
by: XIE, Liang, et al.
Published: (2016)