Real-Time 3D Face Alignment Using an Encoder-Decoder Network With an Efficient Deconvolution Layer
Author(s): Ning, X (Ning, Xin); Duan, PF (Duan, Pengfei); Li, WJ (Li, Weijun); Zhang, SL (Zhang, Shaolin)
Source: IEEE SIGNAL PROCESSING LETTERS Volume: 27 Pages: 1944-1948 DOI: 10.1109/LSP.2020.3032277 Published: 2020
Abstract: In the field of 3D face alignment, most researchers have focused on improving the prediction accuracy of algorithms and ignored the portability for practical applications. To this end, this study presents a real-time 3D face-alignment method that uses an encoder-decoder network with an efficient deconvolution layer. The fusion of the encoding and decoding feature adds more abundant features to this network. An efficient deconvolution layer at the decoding stage applies the L1 norm to select useful features and generate abundant ones through linear operations. Experimental results using the standard AFLW2000-3D and AFLW-LFPA datasets show that our algorithm has low prediction errors with real-time applicability.
Accession Number: WOS:000589190600004
ISSN: 1070-9908
eISSN: 1558-2361
