RGB_IR多模態融合文章MFNet: Towards Real-Time Semantic Segmentation for Autonomous Vehicles with Multi-Spect
MFNet: Towards Real-Time Semantic Segmentation for Autonomous Vehicles with Multi-Spectral Scenes code pytorch 摘要 本文研究了基於新的RGB-Thermal數據集的自動駕駛車輛街景圖像的語義分割，本文還對此進行了介紹。對自動駕駛車輛的興趣日益增加，使得語義分割適應於自動駕駛系統。然而，最
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相關文章
- 1. 2017 IROS之RGBT語義分割：MFNet: Towards Real-Time Semantic Segmentation for Autonomous Vehicles with Multi
- 2. BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
- 3. Encoder-Decoder-with-Atrous-Separable-Convolution-for-Semantic-Image-Segmentation
- 4. Decoders Matter for Semantic Segmentation
- 5. Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art
- 6. 《Understanding Convolution for Semantic Segmentation》
- 7. Context Encoding for Semantic Segmentation
- 8. 論文閱讀：A Slope-robust Cascaded Ground Segmentation in 3D Point Cloud for Autonomous Vehicles
- 9. Understanding Convolution for Semantic Segmentation
- 10. Pyramid Attention Network for Semantic Segmentation