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. ISSN 2162-237X



  • 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
  • Accepted: 27 December 2022
  • Published (online): 6 January 2023
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: 03 Feb 2023 10:42
Status: Published online
Publisher: Institute of Electrical and Electronics Engineers
Refereed: Yes
Identification Number:


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Embargoed until: 6 January 2024

Filename: TNNLS-2022-P-22975.pdf

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