AI RESEARCH
BEVPredFormer: Spatio-temporal Attention for BEV Instance Prediction in Autonomous Driving
arXiv CS.CV
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ArXi:2604.02930v1 Announce Type: new A robust awareness of how dynamic scenes evolve is essential for Autonomous Driving systems, as they must accurately detect, track, and predict the behaviour of surrounding obstacles. Traditional perception pipelines that rely on modular architectures tend to suffer from cumulative errors and latency. Instance Prediction models provide a unified solution, performing Bird's-Eye-View segmentation and motion estimation across current and future frames using information directly obtained from different sensors.