activity
20152023
most citedA Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

262 citations · 743 across the 34 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

eess.IV2020

All-in-Focus Iris Camera With a Great Capture Volume

Kunbo Zhang, Zhenteng Shen, Yunlong Wang +1

Imaging volume of an iris recognition system has been restricting the throughput and cooperation convenience in biometric applications. Numerous improvement trials are still imprac…

cs.CV2020★ 16 cited

Style Intervention: How to Achieve Spatial Disentanglement with Style-based Generators?

Yunfan Liu, Qi Li, Zhenan Sun +1

Generative Adversarial Networks (GANs) with style-based generators (e.g. StyleGAN) successfully enable semantic control over image synthesis, and recent studies have also revealed…

eess.IV2020

Recognition Oriented Iris Image Quality Assessment in the Feature Space

Leyuan Wang, Kunbo Zhang, Min Ren +2

A large portion of iris images captured in real world scenarios are poor quality due to the uncontrolled environment and the non-cooperative subject. To ensure that the recognition…

cs.CV2020★ 8 cited

Black Re-ID: A Head-shoulder Descriptor for the Challenging Problem of Person Re-Identification

Boqiang Xu, Lingxiao He, Xingyu Liao +3

Person re-identification (Re-ID) aims at retrieving an input person image from a set of images captured by multiple cameras. Although recent Re-ID methods have made great success,…

cs.CV2020★ 5 cited

Reference-guided Face Component Editing

Qiyao Deng, Jie Cao, Yunfan Liu +3

Face portrait editing has achieved great progress in recent years. However, previous methods either 1) operate on pre-defined face attributes, lacking the flexibility of controllin…

cs.CV2020

Face Anti-Spoofing by Learning Polarization Cues in a Real-World Scenario

Yu Tian, Kunbo Zhang, Leyuan Wang +1

Face anti-spoofing is the key to preventing security breaches in biometric recognition applications. Existing software-based and hardware-based face liveness detection methods are…