TY - GEN
T1 - SSFD
T2 - 9th IEEE International Conference on Biometrics Theory, Applications and Systems, BTAS 2018
AU - Shi, Lei
AU - Xu, Xiang
AU - Kakadiaris, Ioannis A.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - In this paper, we present a simple but effective face detector (dubbed SSFD), which can localize multi-scale faces. Unlike other multi-scale feature detectors which learn multi-scale features or feature pyramids aggregated from different scale feature maps, SSFD only depends on a single-scale input image and a single-scale feature map to detect faces of various scales. In SSFD, transposed convolutions are leveraged to increase the resolution of feature maps with different strides, which can maintain adequate information for occluded and small faces. In addition, dilated convolutions are deployed to increase the receptive field size, which contributes to obtaining discriminative contextual information. SSFD, which is based on the VGG-16 network, outperforms the ResNet101-based Scale-Face as well as the VGG16-based HR on the WIDER FACE validation dataset.
AB - In this paper, we present a simple but effective face detector (dubbed SSFD), which can localize multi-scale faces. Unlike other multi-scale feature detectors which learn multi-scale features or feature pyramids aggregated from different scale feature maps, SSFD only depends on a single-scale input image and a single-scale feature map to detect faces of various scales. In SSFD, transposed convolutions are leveraged to increase the resolution of feature maps with different strides, which can maintain adequate information for occluded and small faces. In addition, dilated convolutions are deployed to increase the receptive field size, which contributes to obtaining discriminative contextual information. SSFD, which is based on the VGG-16 network, outperforms the ResNet101-based Scale-Face as well as the VGG16-based HR on the WIDER FACE validation dataset.
UR - http://www.scopus.com/inward/record.url?scp=85065410186&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85065410186&partnerID=8YFLogxK
U2 - 10.1109/BTAS.2018.8698570
DO - 10.1109/BTAS.2018.8698570
M3 - Conference contribution
AN - SCOPUS:85065410186
T3 - 2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems, BTAS 2018
BT - 2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems, BTAS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 22 October 2018 through 25 October 2018
ER -