Abstract:
In this paper, an image captioning network is proposed for traffic scene modeling, which incorporates element attention into the encoder-decoder mechanism to generate mor...Show MoreMetadata
Abstract:
In this paper, an image captioning network is proposed for traffic scene modeling, which incorporates element attention into the encoder-decoder mechanism to generate more reasonable scene captions. Firstly, the traffic scene elements are detected and segmented according to their clustered locations. Then, the image captioning network is applied to generate the corresponding caption of each subregion. The static and dynamic traffic elements are appropriately organized to construct a 3D corridor scene model. The semantic relationships between the traffic elements are specified according to the captions. The constructed 3D scene model can be utilized for the offline test of unmanned vehicles. The evaluations and comparisons based on the TSD-max and COCO datasets prove the effectiveness of the proposed framework.
Published in: 2020 IEEE Intelligent Vehicles Symposium (IV)
Date of Conference: 19 October 2020 - 13 November 2020
Date Added to IEEE Xplore: 08 January 2021
ISBN Information: