Neural computation for robust and holographic face detection

Author:

Imani Mohsen1,Zakeri Ali1,Chen Hanning1,Kim TaeHyun2,Poduval Prathyush3,Lee Hyunsei4,Kim Yeseong4,Sadredini Elaheh5,Imani Farhad6

Affiliation:

1. University of California Irvine

2. Pusan National University

3. Indian Institute of Science

4. Daegu Gyeongbuk Institute of Science and Technology

5. University of California Riverside

6. University of Connecticut

Funder

Office of Naval Research

Semiconductor Research Corporation

Air Force Office of Scientific Research

Cisco Systems

NSF (National Science Foundation)

Publisher

ACM

Reference32 articles.

1. Two-stream neural networks for tampered face detection;Zhou P.;CVPRW. IEEE,2017

2. X. He , " Face recognition using laplacianfaces," IEEE transactions on pattern analysis and machine intelligence , vol. 27 , no. 3, pp. 328--340, 2005. X. He et al., "Face recognition using laplacianfaces," IEEE transactions on pattern analysis and machine intelligence, vol. 27, no. 3, pp. 328--340, 2005.

3. An efficient method to face and emotion detection;Reney D.;CSNT. IEEE,2015

4. Z. Wen , " Face relighting with radiance environment maps," in CVPR , vol. 2 . IEEE , 2003 , pp. II-- 158 . Z. Wen et al., "Face relighting with radiance environment maps," in CVPR, vol. 2. IEEE, 2003, pp. II--158.

5. End-to-end 3d face reconstruction with deep neural networks;Dou P.;CVPR,2017

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