| Title |
Comparison of the Methods for Jointly Learning Objects and Actions Using Realtime Object Detector |
| Authors |
홍성준(Sungjun Hong) ; 이희성(Heesung Lee) |
| DOI |
https://doi.org/10.5370/KIEE.2020.69.1.138 |
| Keywords |
Object-action detection; object detection; action detection; joint learning |
| Abstract |
Most of visual detection in videos are limited to focus on objects or human actions separately. In this work, changing the classification loss of well-known realtime object detector, we introduce a detection model to jointly detect object-action pairs in videos. For detecting objects-actions in videos, we present two methods to label object-action pairs, called Cartesian product (CP) and valid Cartesian product (VCP). In experiments on the A2D dataset, we compares results on detection of object-action pairs in terms of the mean average precision. |