说明:We introduce a network that directly predicts the 3D layout of lanes in a road scene from a single image. This
work marks a first attempt to address this task with onboard sensing without assuming a known constant lane
width or relying on pre-mappe <iOrigin> 上传 | 大小:8mb
说明:Training deep models for lane detection is challenging due to the very subtle and sparse supervisory signals in- herent in lane annotations. Without learning from much richer context, these models often fail in challenging sce- narios, e.g., severe o <iOrigin> 上传 | 大小:3mb
说明:Abstract: Lane detection is an important foundation in the development of intelligent vehicles. To address problems such as low detection accuracy of traditional methods and poor real-time performance of deep learning-based methodologies, a lane dete <iOrigin> 上传 | 大小:5mb