AI RESEARCH
A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning
arXiv CS.CV
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ArXi:2605.27884v1 Announce Type: new City-wide traffic forecasting is important for congestion management, route guidance, and intelligent transportation systems, but accurate prediction remains challenging when future traffic must be generated as spatial maps over an entire urban network. Existing traffic movie prediction methods have improved frame-level accuracy, yet many still treat forecasting mainly as image reconstruction.