Learning multi-modal scale-aware attentions for efficient and robust road segmentation
Multi-modal fusion has proven to be beneficial to road segmentation in autonomous driving, where depth is commonly used as complementary data for RGB images to provide robust 3D geometry information. Existing methods adopt an encoder-decoder structure to fuse two modalities for segmentation through...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/159277 |