RGB_IR多模态融合文章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 本文研究了基于新的RGB-Thermal数据集的自动驾驶车辆街景图像的语义分割，本文还对此进行了介绍。对自动驾驶车辆的兴趣日益增加，使得语义分割适应于自动驾驶系统。然而，最
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相关文章
- 1. 2017 IROS之RGBT语义分割：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. 论文阅读：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