• Corpus ID: 211677891

Attention-aware fusion RGB-D face recognition

@article{Uppal2020AttentionawareFR,
  title={Attention-aware fusion RGB-D face recognition},
  author={Hardik Uppal and Alireza Sepas-Moghaddam and Michael A. Greenspan and S. A. Etemad},
  journal={ArXiv},
  year={2020},
  volume={abs/2003.00168}
}
A novel attention aware method is proposed to fuse two image modalities, RGB and depth, for enhanced RGB-D facial recognition. The proposed method uses two attention layers, the first focused on the fused feature maps generated by convolution layers, and the second focused on the spatial features of those maps. The training database is preprocessed and augmented through a set of geometric transformations, and the learning process is further aided using transfer learning from a pure 2D RGB image… 
High-Accuracy RGB-D Face Recognition via Segmentation-Aware Face Depth Estimation and Mask-Guided Attention Network
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The proposed mask-guided RGB-D face recognition model can fully exploit the depth map and segmentation mask information and is more robust against pose variation than previous methods, and outperforms state-of-the-art methods on several public 3D face datasets.

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