Progressive Risk Estimation for Accident Anticipation

Samet Hicsonmez    Eray Çakar    Nermin Samet

   Fatma Güney

NeurIPS 2026

Paper   Code   

Progressive Risk Estimation for Accident Anticipation

Abstract

"Accident anticipation aims to recognize anomalous driving cues before a crash while avoiding false alarms during normal driving. Existing approaches typically formulate this task as binary classification, focusing on whether an accident will occur rather than when it will occur. We propose PRE-ACT, a framework that models accident risk as a continuously evolving signal that increases as the crash approaches. By explicitly enforcing temporal ordering and distance-to-accident awareness, our method progressively raises risk while suppressing premature alarms, leading to significant improvements on MM-AU subsets and Nexar. We further introduce a Separation Score to evaluate the global behavior of predicted risk curves beyond local temporal windows."

BibTeX

@inproceedings{igloss,
      title={Progressive Risk Estimation for Accident Anticipation}, 
      author={Samet Hicsonmez, Eray Çakar, Nermin Samet, Fatma Güney }, 
      journal = {NeurIPS},
      year={2026},
}