A KITTI-based 9,858-frame importance dataset and a model combining driver-intention, semantic, and traffic-rule guidance report large AP gains over prior importance estimation methods.
In: IEEE/CVF International Conference on Computer Vision
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On-Road Object Importance Estimation: A New Dataset and A Model with Multi-Fold Top-Down Guidance
A KITTI-based 9,858-frame importance dataset and a model combining driver-intention, semantic, and traffic-rule guidance report large AP gains over prior importance estimation methods.