Mitigating modality discrepancies for RGB-T semantic segmentation

Han, J., Shenlu, Z., Liu, Y. et al. (2 more authors) (2023) Mitigating modality discrepancies for RGB-T semantic segmentation. IEEE Transactions on Neural Networks and Learning Systems, 35 (7). pp. 9380-9394. ISSN 2162-237X

Abstract

Metadata

Item Type: Article
Authors/Creators:
  • Han, J.
  • Shenlu, Z.
  • Liu, Y.
  • Jiao, Q.
  • Zhang, Q.
Copyright, Publisher and Additional Information:

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.

Keywords: Bridging-then-fusing; contextual information; dataset; modality discrepancy reduction; RGB-T semantic segmentation
Dates:
  • Published: 6 January 2023
  • Published (online): 6 January 2023
  • Accepted: 27 December 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 02 Feb 2023 12:23
Last Modified: 26 Sep 2024 14:34
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Refereed: Yes
Identification Number: 10.1109/TNNLS.2022.3233089
Open Archives Initiative ID (OAI ID):

Export

Statistics