Search Results for author: Caiyong Wang

Found 7 papers, 4 papers with code

Iris Liveness Detection Competition (LivDet-Iris) -- The 2023 Edition

no code implementations6 Oct 2023 Patrick Tinsley, Sandip Purnapatra, Mahsa Mitcheff, Aidan Boyd, Colton Crum, Kevin Bowyer, Patrick Flynn, Stephanie Schuckers, Adam Czajka, Meiling Fang, Naser Damer, Xingyu Liu, Caiyong Wang, Xianyun Sun, Zhaohua Chang, Xinyue Li, Guangzhe Zhao, Juan Tapia, Christoph Busch, Carlos Aravena, Daniel Schulz

New elements in this fifth competition include (1) GAN-generated iris images as a category of presentation attack instruments (PAI), and (2) an evaluation of human accuracy at detecting PAI as a reference benchmark.

DFGC-VRA: DeepFake Game Competition on Visual Realism Assessment

1 code implementation journal 2023 Bo Peng, Xianyun Sun, Caiyong Wang, Wei Wang1, Jing Dong, Zhenan Sun

This paper presents the summary report on the DeepFake Game Competition on Visual Realism Assessment (DFGCVRA).

Face Swapping

Visual Realism Assessment for Face-swap Videos

1 code implementation2 Feb 2023 Xianyun Sun, Beibei Dong, Caiyong Wang, Bo Peng, Jing Dong

Visual realism assessment, or VRA, is essential for assessing the potential impact that may be brought by a specific face-swap video, and it is also important as a quality assessment metric to compare different face-swap methods.

DeepFake Detection Face Swapping

CASIA-Face-Africa: A Large-scale African Face Image Database

no code implementations8 May 2021 Jawad Muhammad, Yunlong Wang, Caiyong Wang, Kunbo Zhang, Zhenan Sun

The proposed database along with its face landmark annotations, evaluation protocols and preliminary results form a good benchmark to study the essential aspects of face biometrics for African subjects, especially face image preprocessing, face feature analysis and matching, facial expression recognition, sex/age estimation, ethnic classification, face image generation, etc.

Age Estimation Face Recognition +3

Joint Iris Segmentation and Localization Using Deep Multi-task Learning Framework

1 code implementation31 Jan 2019 Caiyong Wang, Yuhao Zhu, Yunfan Liu, Ran He, Zhenan Sun

In this paper, we propose a deep multi-task learning framework, named as IrisParseNet, to exploit the inherent correlations between pupil, iris and sclera to boost up the performance of iris segmentation and localization in a unified model.

Iris Segmentation Multi-Task Learning +1

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