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Exploring Event-driven Dynamic Context for Accident Scene Segmentation
[article]
2021
arXiv
pre-print
The robustness of semantic segmentation on edge cases of traffic scene is a vital factor for the safety of intelligent transportation. However, most of the critical scenes of traffic accidents are extremely dynamic and previously unseen, which seriously harm the performance of semantic segmentation methods. In addition, the delay of the traditional camera during high-speed driving will further reduce the contextual information in the time dimension. Therefore, we propose to extract dynamic
arXiv:2112.05006v1
fatcat:xyjr5tiysjgdxbvx2rk2huwdj4