Adding world-model-generated synthetic driving videos to training data, together with a dynamic graph and dilated temporal model, improves accident anticipation accuracy and lead time on multiple benchmarks.
A dynamic spatial-temporal attention network for early anticipation of traffic accidents.IEEE Transactions on Intelligent Transportation Systems, 23(7):9590–9600, 2022
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World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving
Adding world-model-generated synthetic driving videos to training data, together with a dynamic graph and dilated temporal model, improves accident anticipation accuracy and lead time on multiple benchmarks.