1 code implementation • 13 Mar 2024 • Zhangxuan Dang, Yu Zheng, Xinglin Lin, Chunlei Peng, Qiuyu Chen, Xinbo Gao
We consider the problem of anomaly network traffic detection and propose a three-stage anomaly detection framework using only normal traffic.
1 code implementation • 11 Jan 2024 • Chunlei Peng, Boyu Wang, Decheng Liu, Nannan Wang, Ruimin Hu, Xinbo Gao
To address this, we mask the clothing and color information in the personal attribute description extracted through an attribute detection model.
1 code implementation • 18 Dec 2023 • Decheng Liu, Xijun Wang, Chunlei Peng, Nannan Wang, Ruiming Hu, Xinbo Gao
Adversarial attacks involve adding perturbations to the source image to cause misclassification by the target model, which demonstrates the potential of attacking face recognition models.
1 code implementation • 16 Dec 2023 • Decheng Liu, Xu Luo, Chunlei Peng, Nannan Wang, Ruimin Hu, Xinbo Gao
In this paper, we propose a novel Symmetrical Bidirectional Knowledge Alignment for zero-shot sketch-based image retrieval (SBKA).
2 code implementations • 7 Dec 2023 • Chunlei Peng, Huiqing Guo, Decheng Liu, Nannan Wang, Ruimin Hu, Xinbo Gao
Considering the complexity of the quality distribution of both real and fake faces, we propose a novel Deepfake detection framework named DeepFidelity to adaptively distinguish real and fake faces with varying image quality by mining the perceptual forgery fidelity of face images.
no code implementations • 13 Nov 2023 • Qinlin He, Chunlei Peng, Decheng Liu, Nannan Wang, Xinbo Gao
DeepFake detection is pivotal in personal privacy and public safety.
1 code implementation • 21 Jul 2023 • Decheng Liu, Tao Chen, Chunlei Peng, Nannan Wang, Ruimin Hu, Xinbo Gao
Due to the successful development of deep image generation technology, visual data forgery detection would play a more important role in social and economic security.
1 code implementation • 30 Dec 2022 • Decheng Liu, Zeyang Zheng, Chunlei Peng, Yukai Wang, Nannan Wang, Xinbo Gao
Face forgery detection plays an important role in personal privacy and social security.
no code implementations • 30 Oct 2022 • Yu Zheng, Zhangxuan Dang, Chunlei Peng, Chao Yang, Xinbo Gao
In this paper, we propose an MLP-Mixer based multi-view multi-label neural network for network traffic classification.
1 code implementation • 18 Oct 2022 • Decheng Liu, Zhan Dang, Chunlei Peng, Yu Zheng, Shuang Li, Nannan Wang, Xinbo Gao
Experiments conducted on publicly available face forgery detection datasets prove the superior performance of the proposed FedForgery.
1 code implementation • 12 Jul 2022 • Decheng Liu, Weijie He, Chunlei Peng, Nannan Wang, Jie Li, Xinbo Gao
The multiple branches transformer is employed to explore the inter-correlation between different attributes in similar semantic regions for attribute feature learning.
no code implementations • 5 Jul 2022 • Yukai Wang, Chunlei Peng, Decheng Liu, Nannan Wang, Xinbo Gao
In recent years, with the rapid development of face editing and generation, more and more fake videos are circulating on social media, which has caused extreme public concerns.
no code implementations • 9 Jun 2021 • Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao
However, given the continuously evolving attacks, models trained on seen types of adversarial examples generally cannot generalize well to unseen types of adversarial examples.
no code implementations • ICCV 2021 • Dawei Zhou, Nannan Wang, Chunlei Peng, Xinbo Gao, Xiaoyu Wang, Jun Yu, Tongliang Liu
Then, we train a denoising model to minimize the distances between the adversarial examples and the natural examples in the class activation feature space.
no code implementations • 1 Jul 2016 • Chunlei Peng, Xinbo Gao, Nannan Wang, Jie Li
An adaptive sparse graphical representation scheme is designed to represent heterogeneous face images, where a Markov networks model is constructed to generate adaptive sparse vectors.
no code implementations • 2 Mar 2015 • Chunlei Peng, Xinbo Gao, Nannan Wang, Jie Li
Heterogeneous face recognition (HFR) refers to matching face images acquired from different sources (i. e., different sensors or different wavelengths) for identification.