MTMamba++ : Enhancing Multi-Task Dense Scene Understanding via Mamba-Based Decoders
Multi-task dense scene understanding, which trains a model for multiple dense prediction tasks, has a wide range of application scenarios. Capturing long-range dependency and enhancing cross-task interactions are crucial to multi-task dense prediction. In this paper, we propose MTMamba++, a novel ar...
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Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 47(2025), 11 vom: 28. Okt., Seite 10633-10645
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| Auteur principal: |
Lin, Baijiong
(Auteur) |
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| Autres auteurs: |
Jiang, Weisen,
Chen, Pengguang,
Liu, Shu,
Chen, Ying-Cong |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2025
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article |
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