Leveraging spatio-temporal features to forecast time-to-accident
Author:
Affiliation:
1. University of British Columbia, Kelowna, BC, Canada
2. University of Nevada-Las Vegas
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3557915.3565532
Reference5 articles.
1. Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning
2. Fu-Hsiang Chan , Yu-Ting Chen , Yu Xiang , and Min Sun . 2016 . Anticipating accidents in dashcam videos . In Asian Conference on Computer Vision. Springer, 136--153 . Fu-Hsiang Chan, Yu-Ting Chen, Yu Xiang, and Min Sun. 2016. Anticipating accidents in dashcam videos. In Asian Conference on Computer Vision. Springer, 136--153.
3. Anticipating Traffic Accidents with Adaptive Loss and Large-Scale Incident DB
4. Learning Spatiotemporal Features with 3D Convolutional Networks
5. BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Exploring driving behavioral characteristics in pre-, in-, and post-conflict stages based on car-following trajectory data;Ergonomics;2024-08-07
2. Spatio-temporal Analysis of Dashboard Camera Videos for Time-To-Accident Forecasting;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18
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