Virtual Data Generation for Intelligent Driving
ReCamMaster is particularly suitable for generating multi-view training data for autonomous driving systems. Its advantages are: first, it can cost-effectively extend the real collection of single-view road video to generate synchronized material equivalent to multi-camera group shooting; second, it supports the generation of extreme viewing angles (e.g., high elevation), which are difficult to install in practice; and third, it can simulate the imaging effect of different optical parameters, which enhances the robustness of the algorithm.
The typical application process is to use the original video from the car recorder to batch generate multi-view variants such as 45° on the left side and 60° on the right side, while adding environmental effects such as rain and fog. Tests show that the target detection model trained with the dataset enhanced by this method improves the mean accuracy (mAP) in the occlusion scenario by 8.31 TP3 T. Currently there are already autonomous driving teams that use this tool to extend the real data from a single camera into a training set equivalent to an 8-channel camera, which significantly reduces the cost of data acquisition.
This answer comes from the articleReCamMaster: Rendering Tool for Generating Multi-View Videos from a Single VideoThe
English 
简体中文 
日本語 
Deutsch 
Português do Brasil