no code implementations • 3 Jan 2024 • Wei Qian, Chenxu Zhao, Yangyi Li, Fenglong Ma, Chao Zhang, Mengdi Huai
To tackle the aforementioned challenges, in this paper, we design a novel uncertainty modeling framework for self-explaining networks, which not only demonstrates strong distribution-free uncertainty modeling performance for the generated explanations in the interpretation layer but also excels in producing efficient and effective prediction sets for the final predictions based on the informative high-level basis explanations.
no code implementations • 16 Oct 2023 • Chenxu Zhao, Wei Qian, Yucheng Shi, Mengdi Huai, Ninghao Liu
Deep neural networks have exhibited remarkable performance across a wide range of real-world tasks.
no code implementations • 5 May 2023 • Ajian Liu, Zichang Tan, Zitong Yu, Chenxu Zhao, Jun Wan, Yanyan Liang, Zhen Lei, Du Zhang, Stan Z. Li, Guodong Guo
The availability of handy multi-modal (i. e., RGB-D) sensors has brought about a surge of face anti-spoofing research.
no code implementations • 3 Jan 2023 • Hao Fang, Ajian Liu, Jun Wan, Sergio Escalera, Chenxu Zhao, Xu Zhang, Stan Z. Li, Zhen Lei
In order to promote relevant research and fill this gap in the community, we collect a large-scale Surveillance High-Fidelity Mask (SuHiFiMask) dataset captured under 40 surveillance scenes, which has 101 subjects from different age groups with 232 3D attacks (high-fidelity masks), 200 2D attacks (posters, portraits, and screens), and 2 adversarial attacks.
no code implementations • 7 Dec 2022 • Zitong Yu, Chenxu Zhao, Zhen Lei
Face recognition technology has been widely used in daily interactive applications such as checking-in and mobile payment due to its convenience and high accuracy.
1 code implementation • 16 Feb 2022 • Zitong Yu, Ajian Liu, Chenxu Zhao, Kevin H. M. Cheng, Xu Cheng, Guoying Zhao
Can we train a unified model, and flexibly deploy it under various modality scenarios?
no code implementations • 13 Dec 2021 • Junjun Hu, Yanhao Zhu, Bo Zhao, Jiexin Zheng, Chenxu Zhao, Xiangyu Zhu, Kangle Wu, Darun Tang
One of the challenges of logo recognition lies in the diversity of forms, such as symbols, texts or a combination of both; further, logos tend to be extremely concise in design while similar in appearance, suggesting the difficulty of learning discriminative representations.
1 code implementation • 24 Nov 2021 • Zezheng Wang, Zitong Yu, Xun Wang, Yunxiao Qin, Jiahong Li, Chenxu Zhao, Zhen Lei, Xin Liu, Size Li, Zhongyuan Wang
Face anti-spoofing (FAS) plays a crucial role in securing face recognition systems.
no code implementations • 12 Nov 2021 • Yunxiao Qin, Zitong Yu, Longbin Yan, Zezheng Wang, Chenxu Zhao, Zhen Lei
The meta-teacher is trained in a bi-level optimization manner to learn the ability to supervise the PA detectors learning rich spoofing cues.
no code implementations • 16 Aug 2021 • Ajian Liu, Chenxu Zhao, Zitong Yu, Anyang Su, Xing Liu, Zijian Kong, Jun Wan, Sergio Escalera, Hugo Jair Escalante, Zhen Lei, Guodong Guo
The threat of 3D masks to face recognition systems is increasingly serious and has been widely concerned by researchers.
no code implementations • 25 Jul 2021 • Qiang Meng, Xiaqing Xu, Xiaobo Wang, Yang Qian, Yunxiao Qin, Zezheng Wang, Chenxu Zhao, Feng Zhou, Zhen Lei
Despite the great success achieved by deep learning methods in face recognition, severe performance drops are observed for large pose variations in unconstrained environments (e. g., in cases of surveillance and photo-tagging).
3 code implementations • 28 Jun 2021 • Zitong Yu, Yunxiao Qin, Xiaobai Li, Chenxu Zhao, Zhen Lei, Guoying Zhao
Face anti-spoofing (FAS) has lately attracted increasing attention due to its vital role in securing face recognition systems from presentation attacks (PAs).
no code implementations • 13 Apr 2021 • Ajian Liu, Chenxu Zhao, Zitong Yu, Jun Wan, Anyang Su, Xing Liu, Zichang Tan, Sergio Escalera, Junliang Xing, Yanyan Liang, Guodong Guo, Zhen Lei, Stan Z. Li, Du Zhang
To bridge the gap to real-world applications, we introduce a largescale High-Fidelity Mask dataset, namely CASIA-SURF HiFiMask (briefly HiFiMask).
no code implementations • 10 Feb 2021 • Xiaqing Xu, Qiang Meng, Yunxiao Qin, Jianzhu Guo, Chenxu Zhao, Feng Zhou, Zhen Lei
A standard pipeline of current face recognition frameworks consists of four individual steps: locating a face with a rough bounding box and several fiducial landmarks, aligning the face image using a pre-defined template, extracting representations and comparing.
no code implementations • 16 Jul 2020 • Yunxiao Qin, Wei-Guo Zhang, Zezheng Wang, Chenxu Zhao, Jingping Shi
LWAU is inspired by an interesting finding that compared with common deep models, the meta-learner pays much more attention to update its top layer when learning from few images.
1 code implementation • 17 Apr 2020 • Zitong Yu, Yunxiao Qin, Xiaobai Li, Zezheng Wang, Chenxu Zhao, Zhen Lei, Guoying Zhao
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from presentation attacks.
6 code implementations • CVPR 2020 • Zezheng Wang, Zitong Yu, Chenxu Zhao, Xiangyu Zhu, Yunxiao Qin, Qiusheng Zhou, Feng Zhou, Zhen Lei
Depth supervised learning has been proven as one of the most effective methods for face anti-spoofing.
7 code implementations • CVPR 2020 • Jianzhu Guo, Xiangyu Zhu, Chenxu Zhao, Dong Cao, Zhen Lei, Stan Z. Li
Face recognition systems are usually faced with unseen domains in real-world applications and show unsatisfactory performance due to their poor generalization.
6 code implementations • CVPR 2020 • Zitong Yu, Chenxu Zhao, Zezheng Wang, Yunxiao Qin, Zhuo Su, Xiaobai Li, Feng Zhou, Guoying Zhao
Here we propose a novel frame level FAS method based on Central Difference Convolution (CDC), which is able to capture intrinsic detailed patterns via aggregating both intensity and gradient information.
Ranked #4 on Face Anti-Spoofing on OULU-NPU
1 code implementation • 6 Aug 2019 • Chen Ma, Chenxu Zhao, Hailin Shi, Li Chen, Junhai Yong, Dan Zeng
To solve such few-shot problem with the evolving attack, we propose a meta-learning based robust detection method to detect new adversarial attacks with limited examples.
no code implementations • 29 Apr 2019 • Yunxiao Qin, Chenxu Zhao, Xiangyu Zhu, Zezheng Wang, Zitong Yu, Tianyu Fu, Feng Zhou, Jingping Shi, Zhen Lei
Therefore, we define face anti-spoofing as a zero- and few-shot learning problem.
no code implementations • 11 Dec 2018 • Yunxiao Qin, WeiGuo Zhang, Chenxu Zhao, Zezheng Wang, Xiangyu Zhu, Guo-Jun Qi, Jingping Shi, Zhen Lei
In this paper, inspired by the human cognition process which utilizes both prior-knowledge and vision attention in learning new knowledge, we present a novel paradigm of meta-learning approach with three developments to introduce attention mechanism and prior-knowledge for meta-learning.
4 code implementations • CVPR 2019 • Shifeng Zhang, Xiaobo Wang, Ajian Liu, Chenxu Zhao, Jun Wan, Sergio Escalera, Hailin Shi, Zezheng Wang, Stan Z. Li
To facilitate face anti-spoofing research, we introduce a large-scale multi-modal dataset, namely CASIA-SURF, which is the largest publicly available dataset for face anti-spoofing in terms of both subjects and visual modalities.
no code implementations • 19 Nov 2018 • Yunxiao Qin, Chenxu Zhao, Zezheng Wang, Junliang Xing, Jun Wan, Zhen Lei
The method RAML aims to give the Meta learner the ability of leveraging the past learned knowledge to reduce the dimension of the original input data by expressing it into high representations, and help the Meta learner to perform well.
1 code implementation • 13 Nov 2018 • Zezheng Wang, Chenxu Zhao, Yunxiao Qin, Qiusheng Zhou, Guo-Jun Qi, Jun Wan, Zhen Lei
Face anti-spoofing is significant to the security of face recognition systems.
no code implementations • 24 Nov 2014 • Junxiong Wang, Hongzhi Wang, Chenxu Zhao
Currently, many machine learning algorithms contain lots of iterations.