3 accepted papers
Most recognizing occluded faces methods focus on synthetic-occluded faces for training due to the lack of real-occluded data. However, the performance may suffer from degradation since the synthetic-occluded and real-occluded face images are under different distributions. Hence, it draws our eyes to…
Conventional face anti-spoofing methods might be poorly generalized to unseen data distributions. Thus, we improve the generalization of spoof detection from the multi-domain feature disentanglement. Specially, a two-branch convolutional network is proposed to separate spoof-specific features and do…
3D Morphable Model (3DMM) is a statistical tool widely employed in reconstructing 3D face shape. Existing methods are aimed at predicting 3DMM shape parameters with a single encoder but suffer from unclear distinction of different attributes. To address this problem, Two-Pathway Encoder-Decoder Netw…