activity
20182023
most citedExploiting temporal and depth information for multi-frame face anti-spoofing

76 citations · 152 across the 11 of their papers we have counts for

collaborators

11 papers

cs.LG2023

Towards Fair Disentangled Online Learning for Changing Environments

Chen Zhao, Feng Mi, Xintao Wu +4

In the problem of online learning for changing environments, data are sequentially received one after another over time, and their distribution assumptions may vary frequently. Alt…

cs.CR2023

An Automated Vulnerability Detection Framework for Smart Contracts

Feng Mi, Chen Zhao, Zhuoyi Wang +5

With the increase of the adoption of blockchain technology in providing decentralized solutions to various problems, smart contracts have become more popular to the point that bill…

cs.LG2022

Adaptive Fairness-Aware Online Meta-Learning for Changing Environments

Chen Zhao, Feng Mi, Xintao Wu +3

The fairness-aware online learning framework has arisen as a powerful tool for the continual lifelong learning setting. The goal for the learner is to sequentially learn new tasks…

cs.CV2021★ 1 cited

Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face Presentation Attack Detection

Ajian Liu, Chenxu Zhao, Zitong Yu +11

Face presentation attack detection (PAD) is essential to secure face recognition systems primarily from high-fidelity mask attacks. Most existing 3D mask PAD benchmarks suffer from…

cs.LG2020★ 2 cited

A Primal-Dual Subgradient Approachfor Fair Meta Learning

Chen Zhao, Feng Chen, Zhuoyi Wang +1

The problem of learning to generalize to unseen classes during training, known as few-shot classification, has attracted considerable attention. Initialization based methods, such…

cs.CV2020★ 38 cited

Searching Central Difference Convolutional Networks for Face Anti-Spoofing

Zitong Yu, Chenxu Zhao, Zezheng Wang +5

Face anti-spoofing (FAS) plays a vital role in face recognition systems. Most state-of-the-art FAS methods 1) rely on stacked convolutions and expert-designed network, which is wea…

cs.CV2019★ 15 cited

MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks

Chen Ma, Chenxu Zhao, Hailin Shi +3

Deep neural networks (DNNs) are vulnerable to adversarial attack which is maliciously implemented by adding human-imperceptible perturbation to images and thus leads to incorrect p…

cs.AI2019★ 1 cited

Domain Representation for Knowledge Graph Embedding

Cunxiang Wang, Feiliang Ren, Zhichao Lin +3

Embedding entities and relations into a continuous multi-dimensional vector space have become the dominant method for knowledge graph embedding in representation learning. However,…

cs.CV2018★ 18 cited

A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing

Shifeng Zhang, Xiaobo Wang, Ajian Liu +6

Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmar…

cs.LG2018★ 1 cited

Representation based and Attention augmented Meta learning

Yunxiao Qin, Chenxu Zhao, Zezheng Wang +3

Deep learning based computer vision fails to work when labeled images are scarce. Recently, Meta learning algorithm has been confirmed as a promising way to improve the ability of…

cs.CV2018★ 76 cited

Exploiting temporal and depth information for multi-frame face anti-spoofing

Zezheng Wang, Chenxu Zhao, Yunxiao Qin +4

Face anti-spoofing is significant to the security of face recognition systems. Previous works on depth supervised learning have proved the effectiveness for face anti-spoofing. Nev…