Title
Multimodal Future Localization And Emergence Prediction For Objects In Egocentric View With A Reachability Prior
Abstract
In this paper, we investigate the problem of anticipating future dynamics, particularly the future location of other vehicles and pedestrians, in the view of a moving vehicle. We approach two fundamental challenges: (I) the partial visibility due to the egocentric view with a single RGB camera and considerable field-of-view change due to the egomotion of the vehicle: (2) the multimodality of the distribution of fiiture states. In contrast to many previous works, we do not assume structural knowledge from maps. We rather estimate a reachability prior for certain classes of objects from the semantic map of the present image and propagate it into the future using the planned egomotion. Experiments show that the reachability prior combined with multi-hypotheses learning improves multimodal prediction of the future location of tracked objects and, for the first time, the emergence of new objects. We also demonstrate promising zero-shot transfer to unseen datasets.
Year
DOI
Venue
2020
10.1109/CVPR42600.2020.00441
2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)
DocType
ISSN
Citations 
Conference
1063-6919
0
PageRank 
References 
Authors
0.34
35
4
Name
Order
Citations
PageRank
Osama Makansi171.79
Özgün Çiçek22087.83
Kevin Buchicchio300.34
Thomas Brox47866327.52