Predicting Future Spatiotemporal Occupancy Grids with Semantics for Autonomous Driving
IEEE Intelligent Vehicles Symposium（2024）
Key words
Autonomous Vehicles,Occupancy Grid,Future Residents,Prediction Accuracy,Future Conditions,Semantic Segmentation,Prediction Time,High Prediction Accuracy,Environmental Predictors,Prediction Framework,Occupancy State,Longer Time Horizon,Occupational Information,Environmental Conditions,Prediction Model,Convolutional Neural Network,Object Detection,Pedestrian,Point Cloud,Semantic Information,Formal Semantics,Semantic Labels,Upstream Modulator,Prediction Module,Occupancy Probability,Object Labels,Evidence Theory,Semantic Map,Spatio-temporal Prediction,Representation Layer
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