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20152021
most citedPyramidBox++: High Performance Detector for Finding Tiny Face

37 citations · 279 across the 30 of their papers we have counts for

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Showing 2017Show all

9 papers · 1 filter

cs.CV20177 cited

Learning Disentangling and Fusing Networks for Face Completion Under Structured Occlusions

Zhihang Li, Yibo Hu, Ran He

Face completion aims to generate semantically new pixels for missing facial components. It is a challenging generative task due to large variations of face appearance. This paper s…

cs.CV201716 cited

Geometry Guided Adversarial Facial Expression Synthesis

Lingxiao Song, Zhihe Lu, Ran He +2

Facial expression synthesis has drawn much attention in the field of computer graphics and pattern recognition. It has been widely used in face animation and recognition. However,…

cs.CV201711 cited

Adversarial Discriminative Heterogeneous Face Recognition

Lingxiao Song, Man Zhang, Xiang Wu +1

The gap between sensing patterns of different face modalities remains a challenging problem in heterogeneous face recognition (HFR). This paper proposes an adversarial discriminati…

cs.CV2017

Joint Adaptive Neighbours and Metric Learning for Multi-view Subspace Clustering

Nan Xu, Yanqing Guo, Jiujun Wang +2

Due to the existence of various views or representations in many real-world data, multi-view learning has drawn much attention recently. Multi-view spectral clustering methods base…

cs.CV201710 cited

Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification

Yi Li, Lingxiao Song, Xiang Wu +2

Makeup is widely used to improve facial attractiveness and is well accepted by the public. However, different makeup styles will result in significant facial appearance changes. It…

cs.CV201729 cited

Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition

Ran He, Xiang Wu, Zhenan Sun +1

Heterogeneous face recognition (HFR) aims to match facial images acquired from different sensing modalities with mission-critical applications in forensics, security and commercial…