Multi-Label Dilated Recurrent Network for Sequential Face Alignment
Tong Yang, Shizheng Qin, Junchi Yan, Wenqiang Zhang · 2018
Compared with detection in still image, sequential face landmark detection in video is relatively less studied. In this work, we present a novel network with a dilated residual network and a residual convolutional LSTM to preserve the detection acuity at both spatial and temporal dimensions respectively. We also introduce and compare multi-label loss with regression loss and multi-class loss for face landmark detection. We perform extensive experiments to verify the contribution of different components. Our method achieves state-of-the-art performance on benchmark datasets.