Spatial-Temporal Knowledge Integration: Robust Self-Supervised Facial Landmark Tracking

Congcong Zhu
Congcong Zhu
Jide Li
Jide Li
Guangtai Ding
Guangtai Ding

MM '20: The 28th ACM International Conference on Multimedia Seattle WA USA October, 2020, pp. 4135-4143, 2020.

Cited by: 0|Views3
EI

Abstract:

Diversity of training data significantly affects tracking robustness of model under unconstrained environments. However, existing labeled datasets for facial landmark tracking tend to be large but not diverse, and manually annotating the massive clips of new diverse videos is extremely expensive. To address these problems, we propose a Sp...More

Code:

Data:

Your rating :
0

 

Tags
Comments