DICE: Diverse Diffusion Model with Scoring for Trajectory Prediction

Road user trajectory prediction in dynamic environments is a challenging but crucial task for various applications, such as autonomous driving. One of the main challenges in this domain is the multimodal nature of future trajectories stemming from the unknown yet diverse intentions of the agents. Diffusion models have shown to be very effective in capturing such stochasticity in prediction tasks.

Data and Resources

Cite this as

Younwoo Choi, Ray Coden Mercurius, Soheil Mohamad Alizadeh Shabestary, Amir Rasouli (2024). Dataset: DICE: Diverse Diffusion Model with Scoring for Trajectory Prediction. https://doi.org/10.57702/j9s0io3z

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2310.14570
Author Younwoo Choi
More Authors
Ray Coden Mercurius
Soheil Mohamad Alizadeh Shabestary
Amir Rasouli
Homepage https://arxiv.org/abs/2303.01880