Agnostic Lane Detection
Agnostic Lane Detection 翻译 Abstract 车道检测既重要又具有挑战性自动驾驶任务受很多因素的影响因素，例如光线条件，其他因素造成的遮挡车辆，道路上不相关的标记和固有车道的长而细的特性。传统方法通常将车道检测视为语义分割任务，该任务将类别标签分配给图像的每个像素。 这种表述在很大程度上取决于以下假设： 车道数量是预先定义和固定的，不会发生车道变化，这并不总是成立。 为了
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相关文章
- 1. 转：awesome-lane-detection
- 2. 【翻译】New Lane Model and Distance Transform for Lane Detection and Tracking
- 3. 3D-LaneNet: End-to-End 3D Multiple Lane Detection
- 4. A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content
- 5. Domain agnostic feature learning
- 6. 【Papers】Robust Lane Detection via Expanded Self Attention 论文解读
- 7. 车道线-论文阅读: Learning Lightweight Lane Detection CNNs by Self Attention Distillation
- 8. 【论文笔记】 Towards End-to-End Lane Detection: an Instance SegmentationApproach
- 9. 《Key Points Estimation and Point Instance Segmentation Approach for Lane Detection》翻译
- 10. 车道线检测——Efficient Road Lane Marking Detection With Deep Learning