PROCÉDÉ DE DÉTECTION D'UNE BOÎTE DE LIMITATION EN PSEUDO-3D À BASE DE CNN POUVANT CONVERTIR DES MODES EN FONCTION DE POSES D'OBJETS À L'AIDE DE SEGMENTATION D'INSTANCES ET DISPOSITIF L'UTILISANT

摘要

A method for detecting a pseudo-3D bounding box based on a CNN capable of converting modes according to poses of detected objects using an instance segmentation is provided to be used for realistic rendering in virtual driving. Shade information of each of surfaces of the pseudo-3D bounding box can be reflected on the learning according to this method. The pseudo-3D bounding box may be obtained through a lidar or a rader, and the surface may be segmented by using a camera. The method includes steps of: a learning device instructing a pooling layer to apply pooling operations to a 2D bounding box region, thereby generating a pooled feature map, and instructing an FC layer to apply neural network operations thereto; instructing a convolutional layer to apply convolution operations to surface regions; and instructing a FC loss layer to generate class losses and regression losses.