RGB模态中的不确定权重WR可以计算为: 不确定性感知跨模态检测器(CMDet) 本文选择ROITransformer作为基准算法,并修改为跨模态检测器来解决跨模态输入问题。UA-CMDet的输入是一对RGB-Infrared图像,送入特征提取器中。本文将两个模态提取的特征图送入跨模态融合模块,生成一系列包含跨模态知识的特征图。在跨模态融合模块...
To fill this gap, we constructed a large-scale drone-based RGB-infrared vehicle detection dataset called DroneVehicle, which contains 28, 439 RGB-infrared image pairs covering urban roads, residential areas, parking lots, and other scenarios from day to night. Cross-modal images provide ...
Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning - VisDrone/DroneVehicle
用infrared的框来弥补对应的可见光所在的框。 对于跨模态检测,特别是针对可见光模态,光照条件同样能影响RGB图像的不确定性。作者提出w_{iv}来量化这种不确定权重。权重是通过灰度直方图来计算。 Implement details 作者选用的Baseline是RoiTransformer的架构,并在这个基础上修改了网络架构并使其适应跨模态的输入和输出。C...
As a large-scale dataset with both RGB and thermal infrared (RGBT) images, the benchmark enables extensive evaluation and investigation of visual analysis algorithms on the drone platform. In particular, we design two popular tasks with the benchmark, including object detection and object counting...
Meanwhile, the use of a simple RGB sensor, not a complex integration of multiple or expensive sensors [i.e., multispectral and LiDAR (light detection and ranging)], makes it more applicable and user-friendly for the farmers, farming, and the economic sustainability of many economically and ...
from day to night. Specifically, DroneVehicle consists of 15,532 pairs of images, i.e., RGB images and infrared images with rich annotations, including oriented object bounding boxes, object categories, etc. With intensive amount of effort, our benchmark has 441,642 annotated instances in 31,...
As a large-scale dataset with both RGB and thermal infrared (RGBT) images, the benchmark enables extensive evaluation and investigation of visual analysis algorithms on the drone platform. In particular, we design two popular tasks with the benchmark, including object detection and object counting...
RGB可见图像上的SS2D示意图。最初,图像通过扫描扩展,产生四个不同的特征序列。然后这些序列由 S6 Block处理。最后,通过扫描合并S6 Block的输出以创建最终的 2D 特征图。 SS2D 目的:扫描扩展用于生成不同的排列方式或视角来捕获图像块的多样信息,以提高后续融合过程的效果。 步骤:每个输入块根据不同的扫描顺序(如...
After acquiring scan datasets, they converted RGB images to 8-bit grayscale images, and identified boundaries of particles based on the fact that boundaries of rocks are darker than the interiors in the grayscale images. Based on the diameters of the particles, they estimated the permeability of...