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DRIVE: Deep Reinforced Accident Anticipation with Visual Explanation

  • Published:2021-10 Issue: Volume: Page:
  • ISSN:
  • Container-title:2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • language:
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Author:

Bao Wentao1,Yu Qi1,Kong Yu1

Affiliation:

1. Rochester Institute of Technology,Golisano College of Computing and Information Sciences

Funder

Office of Naval Research

Army Research Office

Publisher

IEEE

Reference50 articles.

1. Very deep convolutional networks for large-scale image recognition;simonyan,2014

2. CADP: A Novel Dataset for CCTV Traffic Camera based Accident Analysis

3. Recur-rent models of visual attention;mnih;NeurIPS,2014

4. Asynchronous methods for deep reinforcement learning;mnih;ICML,2016

5. Corso. TASED-Net: Temporally-aggregating spatial encoder-decoder network for video saliency detection;min;ICCV,2019

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2. Explainable reinforcement learning (XRL): a systematic literature review and taxonomy;Machine Learning;2023-11-29

3. STRIDE: Street View-based Environmental Feature Detection and Pedestrian Collision Prediction;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

4. An End-to-End Online Traffic-Risk Incident Prediction in First-Person Dash Camera Videos;Big Data and Cognitive Computing;2023-07-06

5. Reinforcement Learning for Predicting Traffic Accidents;2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC);2023-02-20
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