| Paper ID | SS-5.5 |
| Paper Title |
DUAL METRIC DISCRIMINATOR FOR OPEN SET VIDEO DOMAIN ADAPTATION |
| Authors |
Yatian Wang, Didi Chuxing, China; Xiaolin Song, Tianjin University, China; Yezhen Wang, Pengfei Xu, Runbo Hu, Hua Chai, Didi Chuxing, China |
| Session | SS-5: Domain Adaptation for Multimedia Signal Processing |
| Location | Gather.Town |
| Session Time: | Wednesday, 09 June, 13:00 - 13:45 |
| Presentation Time: | Wednesday, 09 June, 13:00 - 13:45 |
| Presentation |
Poster
|
| Topic |
Special Sessions: Domain Adaptation for Multimedia Signal Processing |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
Existing video domain adaptation methods focus on addressing closed set problems. However, it is nearly impossible to guarantee different domains share exactly the same set of categories in realistic scenarios. Hence, open set video domain adaptation (OSVDA) problem, which involves unknown categories, has achieved increasingly close attention. In this paper, we propose a seminal framework, which involves spatial and temporal information to address OSVDA problem. Besides, we design a novel discrimination module, i.e., Dual Metric Discriminator (DMD), to separate known and unknown categories based on implicit and explicit similarity metrics. We conduct comprehensive experiments on several benchmarks and achieve state-of-the-art performance with 40.4%, 33.7%, and 79.2% accuracy on UCF to HMDB, HMDB to UCF, and Kinetics to UCF scenarios respectively. |
