图像特征:The C5 feature (output of 5th stage) is upsampled and fused with C4 feature (output of 4th stage) to produce the P4 feature. The P4 feature with 1/16 input resolution is used as the 2D feature. 所以最终的图像特征图是
作者首先说明没有image guidance module,网络也取得了不错的结果,但是为了更好的利用图像丰富的语义信息,作者在object queries初始化这里加入了image guidance ,image features作为K,V,lidar BEV features作为查询,这样通过transformer得到了lidar-camera BEV features(F_{LC}).然后利用F_{LC}生成heatmap,进行object que...
Modern manufacturing facilities need advanced technology for automation and efficiency. With defect detection accuracy as good as 0.1mm, the D405 enables automated inspections you can trust, as well as high precision pick and place for small objects at close range to keep business moving. ...
6-DoF visual-inertial stereo SLAM with advanced sensor fusion and thermal compensation Object Detection Object Types Persons, Vehicles Custom Objects Object Tracking Yes Detection Outputs Bounding Boxes 2D/3D Location Speed Unique ID Segmentation Masks ...
(3)贡献了Object Depth via Motion and Detection数据集。 论文核心 Depth from Motion and Detection Model 模型输入 xi, yi, wi,hi分别表示为第i次观测的图像边框中心坐标、宽度和高度,Pi为相机的相应位置。 相机模型 可以参考相机模型的知识:https://zhuanlan.zhihu.com/p/52322904 ...
Autonomous driving has been widely applied in commercial and industrial applications, along with the upgrade of environmental awareness systems. Tasks such as path planning, trajectory tracking, and obstacle avoidance are strongly dependent on the ability to perform real-time object detection and position...
BEV空间的数据量是image空间的1/6,容易过拟合,需要在BEV空间做数据增强(view transformer阻断了数据增强的影响范围 Pipeline Performance ![assets/BEVDet_ High-performance Multi-camera 3D Object Detection in Bird-Eye-View/image-20240118190826418.png]]
3D perception based on the representations learned from multi-camera bird's-eye-view (BEV) is trending as cameras are cost-effective for mass production in autonomous driving industry. However, there exists a distinct performance gap between multi-camera BEV and LiDAR based 3D object detection. On...
I used YOLO v3 when I first started the object counting project which gave me about ~10FPS with tracking, making it difficult to run more than one stream at a time. Using YOLO v4 made it much easier to run two streams with a higher resolution, as well as giving a better detection acc...
AI-powered motion detection (facial recognition and object detection are optional) Supports USB webcams and ONVIF IP cameras Event-triggered video capture Scheduled recording Mobile- and web-based user interface Integrates with cloud storage - Dropbox, Google Drive, and iSpyCloud ...