Pedestrian Crossing Prediction With Pathwise Feature Fusion and Stacked Gate Recurrent Unit
Author:
Affiliation:
1. Xi'an University of Posts, Telecommunications, Xi'an, China
2. Tsinghua University, Beijing, China
3. Society of Automotive Engineers, Beijing, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7782634/10389610/10379824.pdf?arnumber=10379824
Reference13 articles.
1. Are They Going to Cross? A Benchmark Dataset and Baseline for Pedestrian Crosswalk Behavior
2. Learning Spatiotemporal Features with 3D Convolutional Networks
3. Empirical evaluation of gated recurrent neural networks on sequence modeling;Chung,2014
4. PIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and Trajectory Prediction
5. Pedestrian action anticipation using contextual feature fusion in stacked RNNs;Rasouli,2019
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