此外,通过上述的实验结果可以看出,与单独使用图像或仅依赖激光雷达点云数据相比,DV-3DLane算法模型显著提高了车道线的检测性能。值得注意的是,我们的方法在所有指标上都显著超越了仅使用激光雷达作为输入为LATR算法模型配备的配置,凸显了DV-3DLane算法模型在利用两种模式的信息方面取得的重大改进。 下表展示了我们提出的...
这部分就是标准的self attention加cross attention部分,不细说了。 总结: LATR在openlane数据集上效果确实不错,但是我在自己数据集上训练收敛很慢,效果比较差。使用PV域的车道线实例分割辅助head,并把PV域的bipartite matching结果作为3D车道线lane query和GT的匹配结果,这部分我比较认可,PV也可以当成一个辅助部分。3D...
Robust 3D lane detection is the key to advanced autonomous driving technologies. However, complex traffic scenes such as bad weather and variable terrain are the main factors affecting the robustness of lane detection algorithms. In this paper, a generalized two-stage network called Att-Gen-LaneNet...
该框架包括RadarBEVNet用于雷达BEV特征提取和Cross-Attention Multi-layer Fusion Module (CAMF)用于在BEV空间中进行鲁棒雷达-摄像头特征融合。 基于RCBEVDet,作者进一步提出了RCBEVDet++感知框架,该框架扩展了CAMF模块以容纳基于 Query 的多视摄像头感知模型,并充分发挥了RCBEVDet在各种3D感知任务中的全部潜力。 在nuSc...
“Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection” “M3DSSD: Monocular 3D Single Stage Object Detector” “PointPillars: Fast Encoders for Object Detection from Point Clouds” “Joint 3D Proposal Generation and Object Detection from View Aggregation” ...
关键词:3D 卷积神经网络;伪 3D 卷积;全局平均池化;注意力机制;疲劳驾驶 Driving fatigue detection based on pseudo 3D convolutional neural network and attention mechanisms Zhuang Yuan, Qi Yong School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China ...
# init with pre-trained model weights when training args.pretrained = False # apply batch norm in network args.batch_norm = True # attention args.position_embedding = 'learned' args.use_att = True args.use_proj = True args.num_proj = 4 args.num_att = 1 args.use_att = True args....
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大家都在dense BEV上面做感知任务,放出组内小伙伴最近的工作,使用sparse curve query来做3d 车道线检测。受DAB-DETR启发,把车道线描述成anchor curve (ordered point set),使用curve cross attention,迭代车…
后续方向一定是BEV空间的端到端检测LATR: 3D Lane Detection from Monocular Images with Transformer文献...