Part-Activated Deep Reinforcement Learning for Action Prediction

By Lei Chen, Jiwen Lu, Zhanjie Song, Jie Zhou. 2018

50 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Reinforcement Learning

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Shiji Song
2. Yulin Wang
3. Gao Huang
4. Le Yang
5. Yizeng Han
6. Honghui Wang
7. John K. Tsotsos
8. Xiao Tan

In Computer Vision and Pattern Recognition

1. Shiji Song
2. John K. Tsotsos
3. Yulin Wang
4. Gao Huang
5. Yizeng Han
6. Amir Rasouli
7. Le Yang
8. Iuliia Kotseruba

In Reinforcement Learning

1. Gao Huang
2. John K. Tsotsos

Citations in the corpus

• Dynamic Neural Networks: A Survey (2021, background): “Sa & Sp & Te Classification [196], [197], Frame interpolation [234], [235], Super resolution [236], Video deblurring [237], [238], Action prediction [239]”
• Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition (2019, background): “anticipation in [14], for natural language grounding in [19] and for video description in [46]. Our work is most closely related to the ones that use reinforcement learning for action recognition. In [4], the part activation policy of human body parts is learned with RL for action prediction. [40] f”
• PIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and Trajectory Prediction (2019, background): “In the computer vision community there is a large body of works dedicated to video and action prediction [20, 19, 24, 21, 7, 5, 17].”