Multitask Adaptation for Unlabeled Domain Using Multiple Single-Task Domains
Semantic segmentation and depth estimation tasks are crucial for autonomous driving systems, but obtaining their labels from real-world datasets is costly. To address the problem, we developed a multitask domain adaptation that uses various labeled datasets with distinct tasks to adapt the multitask...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10804160/ |
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