Original paper
End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning
Volume: 42, Issue: 6, Pages: 1317 - 1332
Published: Feb 14, 2019
Abstract
We study active object tracking, where a tracker takes visual observations (i.e., frame sequences) as input and produces the corresponding camera control signals as output (e.g., move forward, turn left, etc.). Conventional methods tackle tracking and camera control tasks separately, and the resulting system is difficult to tune jointly. These methods also require significant human efforts for image labeling and expensive trial-and-error system...
Paper Details
Title
End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning
Published Date
Feb 14, 2019
Volume
42
Issue
6
Pages
1317 - 1332