Abstract: Aiming at the low accuracy of traditional instance segmentation methods in handling multi-object segmentation in unmanned driving technology, we proposed a deep learning method based on joint attention mechanism to achieve instance segmentation of urban traffic multi-object scenes. The method in tegrated channel attention and spatial attention by designing the joint attention module,  guided the neural network branches to process important feature information, so as to improve the performance of the network for multi-scale object segmentation, and solved the problem of poor segmentation effect of the current deep learning network for urban traffic multi-object scene. The  experimental results on cityscape dataset show that  the proposed method is effective and  can improve the accuracy of instance segmentation by unmanned driving technology in urban road traffic scenes.

Key words: instance segmentation, attention mechanism, road scene segmentation, deep learning