Research and application of Faster RCNN-based video action detection model
Author:
Affiliation:
1. Beijing Jingneng Energy Technology Research Co, Ltd.,Beijing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10483274/10483325/10483516.pdf?arnumber=10483516
Reference10 articles.
1. Faster r-cnn: Towards real-time object detection with region proposal networks [J];Ren;Advances in neural information processing systems,2015
2. Ventral-Dorsal Neural Networks: Object Detection Via Selective Attention
3. Where, When, and How: Are they all sensorimotor? Towards a unified view of the dorsal pathway in vision and audition
4. Beyond Frame-level CNN: Saliency-Aware 3-D CNN With LSTM for Video Action Recognition
5. Intelligent video anomaly detection and classification using faster RCNN with deep reinforcement learning model
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