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ProIn: Learning to Predict Trajectory Based on Progressive Interactions for Autonomous Driving
In this work, a progressive interaction network is proposed to enable the agent's feature to progressively focus on relevant maps, in order to better learn agents' feature representation capturing the relevant map constraints.
IDAN: Image Difference Attention Network for Change Detection
In the image preprocessing stage, we use a pre-training model to extract the feature differences between two input images to obtain the feature difference map (FD-map), and Canny for edge detection to obtain the edge difference map (ED-map).
Road detection via a dual-task network based on cross-layer graph fusion modules
Road detection based on remote sensing images is of great significance to intelligent traffic management.
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