no code implementations • 22 Mar 2023 • Zexin Li, Bangjie Yin, Taiping Yao, Juefeng Guo, Shouhong Ding, Simin Chen, Cong Liu
A hard challenge in developing practical face recognition (FR) attacks is due to the black-box nature of the target FR model, i. e., inaccessible gradient and parameter information to attackers.
no code implementations • 8 Mar 2023 • Guanshuo Wang, Fufu Yu, Junjie Li, Qiong Jia, Shouhong Ding
Text-based Person Search (TPS), is targeted on retrieving pedestrians to match text descriptions instead of query images.
1 code implementation • 4 Mar 2023 • Suhang Ye, Yingyi Zhang, Jie Hu, Liujuan Cao, Shengchuan Zhang, Lei Shen, Jun Wang, Shouhong Ding, Rongrong Ji
Specifically, DistilPose maximizes the transfer of knowledge from the teacher model (heatmap-based) to the student model (regression-based) through Token-distilling Encoder (TDE) and Simulated Heatmaps.
no code implementations • 19 Feb 2023 • Jie Zhang, Bo Li, Chen Chen, Lingjuan Lyu, Shuang Wu, Shouhong Ding, Chao Wu
In this work, we propose a novel algorithm called Decision Boundary based Federated Adversarial Training (DBFAT), which consists of two components (local re-weighting and global regularization) to improve both accuracy and robustness of FL systems.
no code implementations • 7 Dec 2022 • Yinpeng Dong, Peng Chen, Senyou Deng, Lianji L, Yi Sun, Hanyu Zhao, Jiaxing Li, Yunteng Tan, Xinyu Liu, Yangyi Dong, Enhui Xu, Jincai Xu, Shu Xu, Xuelin Fu, Changfeng Sun, Haoliang Han, Xuchong Zhang, Shen Chen, Zhimin Sun, Junyi Cao, Taiping Yao, Shouhong Ding, Yu Wu, Jian Lin, Tianpeng Wu, Ye Wang, Yu Fu, Lin Feng, Kangkang Gao, Zeyu Liu, Yuanzhe Pang, Chengqi Duan, Huipeng Zhou, Yajie Wang, Yuhang Zhao, Shangbo Wu, Haoran Lyu, Zhiyu Lin, YiFei Gao, Shuang Li, Haonan Wang, Jitao Sang, Chen Ma, Junhao Zheng, Yijia Li, Chao Shen, Chenhao Lin, Zhichao Cui, Guoshuai Liu, Huafeng Shi, Kun Hu, Mengxin Zhang
The security of artificial intelligence (AI) is an important research area towards safe, reliable, and trustworthy AI systems.
1 code implementation • European Conference on Computer Vision 2022 • Zhaoyu Chen, Bo Li, Shuang Wu, Jianghe Xu, Shouhong Ding, Wenqiang Zhang
Though deep neural networks (DNNs) have demonstrated excellent performance in computer vision, they are susceptible and vulnerable to carefully crafted adversarial examples which can mislead DNNs to incorrect outputs.
no code implementations • 13 Oct 2022 • Shuai Jia, Bangjie Yin, Taiping Yao, Shouhong Ding, Chunhua Shen, Xiaokang Yang, Chao Ma
For face recognition attacks, existing methods typically generate the l_p-norm perturbations on pixels, however, resulting in low attack transferability and high vulnerability to denoising defense models.
7 code implementations • 5 Oct 2022 • Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.
no code implementations • 28 Sep 2022 • Xintian Wu, Hanbin Zhao, Liangli Zheng, Shouhong Ding, Xi Li
Existing methods mainly extract the text information from only one sentence to represent an image and the text representation effects the quality of the generated image well.
no code implementations • 25 Sep 2022 • Bo Li, Lv Tang, Senyun Kuang, Mofei Song, Shouhong Ding
In this paper, we present a novel model for simultaneous stable co-saliency detection (CoSOD) and object co-segmentation (CoSEG).
no code implementations • 25 Sep 2022 • Dongli Tan, Jiang-Jiang Liu, Xingyu Chen, Chao Chen, Ruixin Zhang, Yunhang Shen, Shouhong Ding, Rongrong Ji
In this paper, we propose an efficient structure named Efficient Correspondence Transformer (ECO-TR) by finding correspondences in a coarse-to-fine manner, which significantly improves the efficiency of functional correspondence model.
1 code implementation • 1 Sep 2022 • Jie Zhang, Zhiqi Li, Bo Li, Jianghe Xu, Shuang Wu, Shouhong Ding, Chao Wu
Extensive experiments on federated datasets and real-world datasets demonstrate that FedLC leads to a more accurate global model and much improved performance.
1 code implementation • 25 Jul 2022 • Junjie Li, Yichao Yan, Guanshuo Wang, Fufu Yu, Qiong Jia, Shouhong Ding
In this paper, we take a further step and present Domain Adaptive Person Search (DAPS), which aims to generalize the model from a labeled source domain to the unlabeled target domain.
no code implementations • 20 Jul 2022 • Qianyu Zhou, Ke-Yue Zhang, Taiping Yao, Ran Yi, Shouhong Ding, Lizhuang Ma
Existing DG-based FAS approaches always capture the domain-invariant features for generalizing on the various unseen domains.
no code implementations • 20 Jul 2022 • Qianyu Zhou, Ke-Yue Zhang, Taiping Yao, Ran Yi, Kekai Sheng, Shouhong Ding, Lizhuang Ma
Most existing UDA FAS methods typically fit the trained models to the target domain via aligning the distribution of semantic high-level features.
1 code implementation • 15 Jul 2022 • Yuxi Mi, Yuge Huang, Jiazhen Ji, Hongquan Liu, Xingkun Xu, Shouhong Ding, Shuigeng Zhou
To compensate, the method introduces a plug-in interactive block to allow attention transfer from the client-side by producing a feature mask.
1 code implementation • 15 Jul 2022 • Jiazhen Ji, Huan Wang, Yuge Huang, Jiaxiang Wu, Xingkun Xu, Shouhong Ding, Shengchuan Zhang, Liujuan Cao, Rongrong Ji
This paper proposes a privacy-preserving face recognition method using differential privacy in the frequency domain.
1 code implementation • CVPR 2022 • Yuge Huang, Jiaxiang Wu, Xingkun Xu, Shouhong Ding
Inspired by the ultimate goal of KD methods, we propose a novel Evaluation oriented KD method (EKD) for deep face recognition to directly reduce the performance gap between the teacher and student models during training.
no code implementations • CVPR 2022 • Shuai Jia, Chao Ma, Taiping Yao, Bangjie Yin, Shouhong Ding, Xiaokang Yang
In addition, the proposed frequency attack enhances the transferability across face forgery detectors as black-box attacks.
1 code implementation • CVPR 2022 • Xuehui Wang, Kai Zhao, Ruixin Zhang, Shouhong Ding, Yan Wang, Wei Shen
In this framework, annotated masks of seen categories and pseudo masks of unseen categories serve as a prior for contrastive learning, where features from the mask regions (foreground) are pulled together, and are contrasted against those from the background, and vice versa.
no code implementations • CVPR 2022 • Zhaoyu Chen, Bo Li, Jianghe Xu, Shuang Wu, Shouhong Ding, Wenqiang Zhang
To move towards a practical certifiable patch defense, we introduce Vision Transformer (ViT) into the framework of Derandomized Smoothing (DS).
no code implementations • 11 Mar 2022 • Kai Zhao, Lei Shen, Yingyi Zhang, Chuhan Zhou, Tao Wang, Ruixin Zhang, Shouhong Ding, Wei Jia, Wei Shen
In this paper, by observing that palmar creases are the key information to deep-learning-based palmprint recognition, we propose to synthesize training data by manipulating palmar creases.
1 code implementation • CVPR 2022 • Jie Zhang, Bo Li, Jianghe Xu, Shuang Wu, Shouhong Ding, Lei Zhang, Chao Wu
The proposed method can efficiently imitate the target model through a small number of queries and achieve high attack success rate.
no code implementations • CVPR 2022 • Junyi Cao, Chao Ma, Taiping Yao, Shen Chen, Shouhong Ding, Xiaokang Yang
Reconstruction learning over real images enhances the learned representations to be aware of forgery patterns that are even unknown, while classification learning takes the charge of mining the essential discrepancy between real and fake images, facilitating the understanding of forgeries.
1 code implementation • CVPR 2022 • Yijie Zhong, Bo Li, Lv Tang, Senyun Kuang, Shuang Wu, Shouhong Ding
We first design a novel frequency enhancement module (FEM) to dig clues of camouflaged objects in the frequency domain.
1 code implementation • 30 Dec 2021 • Shice Liu, Shitao Lu, Hongyi Xu, Jing Yang, Shouhong Ding, Lizhuang Ma
However, the improvement is still limited by two issues: 1) It is difficult to perfectly map all faces to a shared feature space.
no code implementations • 28 Dec 2021 • Qiqi Gu, Shen Chen, Taiping Yao, Yang Chen, Shouhong Ding, Ran Yi
The progressive enhancement process facilitates the learning of discriminative features with fine-grained face forgery clues.
no code implementations • 27 Dec 2021 • Ke Sun, Taiping Yao, Shen Chen, Shouhong Ding, Jilin L, Rongrong Ji
With various facial manipulation techniques arising, face forgery detection has drawn growing attention due to security concerns.
1 code implementation • 23 Dec 2021 • Jie Zhang, Chen Chen, Bo Li, Lingjuan Lyu, Shuang Wu, Shouhong Ding, Chunhua Shen, Chao Wu
One-shot Federated Learning (FL) has recently emerged as a promising approach, which allows the central server to learn a model in a single communication round.
no code implementations • 25 Oct 2021 • Yijie Zhong, Bo Li, Lv Tang, Hao Tang, Shouhong Ding
With a lightweight basic convolution block, we build a two-stages framework: Segmentation Network (SN) is designed to capture sufficient semantics and classify the pixels into unknown, foreground and background regions; Matting Refine Network (MRN) aims at capturing detailed texture information and regressing accurate alpha values.
no code implementations • 4 Sep 2021 • Zhihao Gu, Yang Chen, Taiping Yao, Shouhong Ding, Jilin Li, Feiyue Huang, Lizhuang Ma
To address this issue, we term this task as a Spatial-Temporal Inconsistency Learning (STIL) process and instantiate it into a novel STIL block, which consists of a Spatial Inconsistency Module (SIM), a Temporal Inconsistency Module (TIM), and an Information Supplement Module (ISM).
2 code implementations • ICCV 2021 • Lv Tang, Bo Li, Shouhong Ding, Mofei Song
As a pixel-wise classification task, LRSCN is designed to capture sufficient semantics at low-resolution to identify the definite salient, background and uncertain image regions.
Ranked #6 on RGB Salient Object Detection on DAVIS-S
no code implementations • 5 Aug 2021 • Shubao Liu, Ke-Yue Zhang, Taiping Yao, Mingwei Bi, Shouhong Ding, Jilin Li, Feiyue Huang, Lizhuang Ma
However, little attention has been paid to the feature extraction process for the FAS task, especially the influence of normalization, which also has a great impact on the generalization of the learned representation.
no code implementations • 22 Jul 2021 • Ke-Yue Zhang, Taiping Yao, Jian Zhang, Shice Liu, Bangjie Yin, Shouhong Ding, Jilin Li
In pursuit of consolidating the face verification systems, prior face anti-spoofing studies excavate the hidden cues in original images to discriminate real persons and diverse attack types with the assistance of auxiliary supervision.
no code implementations • 30 Jun 2021 • Shubao Liu, Ke-Yue Zhang, Taiping Yao, Kekai Sheng, Shouhong Ding, Ying Tai, Jilin Li, Yuan Xie, Lizhuang Ma
Face anti-spoofing approaches based on domain generalization (DG) have drawn growing attention due to their robustness for unseen scenarios.
1 code implementation • 7 May 2021 • Bangjie Yin, Wenxuan Wang, Taiping Yao, Junfeng Guo, Zelun Kong, Shouhong Ding, Jilin Li, Cong Liu
Deep neural networks, particularly face recognition models, have been shown to be vulnerable to both digital and physical adversarial examples.
no code implementations • 6 May 2021 • Zhihong Chen, Taiping Yao, Kekai Sheng, Shouhong Ding, Ying Tai, Jilin Li, Feiyue Huang, Xinyu Jin
Face anti-spoofing approach based on domain generalization(DG) has drawn growing attention due to its robustness forunseen scenarios.
no code implementations • 6 May 2021 • Shen Chen, Taiping Yao, Yang Chen, Shouhong Ding, Jilin Li, Rongrong Ji
Specifically, we propose a Multi-scale Patch Similarity Module (MPSM), which measures the similarity between features of local regions and forms a robust and generalized similarity pattern.
no code implementations • CVPR 2021 • Wenxuan Wang, Bangjie Yin, Taiping Yao, Li Zhang, Yanwei Fu, Shouhong Ding, Jilin Li, Feiyue Huang, xiangyang xue
Previous substitute training approaches focus on stealing the knowledge of the target model based on real training data or synthetic data, without exploring what kind of data can further improve the transferability between the substitute and target models.
2 code implementations • 18 Feb 2021 • Liming Jiang, Zhengkui Guo, Wayne Wu, Zhaoyang Liu, Ziwei Liu, Chen Change Loy, Shuo Yang, Yuanjun Xiong, Wei Xia, Baoying Chen, Peiyu Zhuang, Sili Li, Shen Chen, Taiping Yao, Shouhong Ding, Jilin Li, Feiyue Huang, Liujuan Cao, Rongrong Ji, Changlei Lu, Ganchao Tan
This paper reports methods and results in the DeeperForensics Challenge 2020 on real-world face forgery detection.
no code implementations • 1 Feb 2021 • Jian Zhang, Ying Tai, Taiping Yao, Jia Meng, Shouhong Ding, Chengjie Wang, Jilin Li, Feiyue Huang, Rongrong Ji
Face authentication on mobile end has been widely applied in various scenarios.
no code implementations • ECCV 2020 • Ke-Yue Zhang, Taiping Yao, Jian Zhang, Ying Tai, Shouhong Ding, Jilin Li, Feiyue Huang, Haichuan Song, Lizhuang Ma
Face anti-spoofing is crucial to security of face recognition systems.
no code implementations • 5 Feb 2020 • Chengwei Chen, Pan Chen, Haichuan Song, Yiqing Tao, Yuan Xie, Shouhong Ding, Lizhuang Ma
Anomaly detection is a fundamental problem in computer vision area with many real-world applications.
no code implementations • 27 Feb 2019 • Yao Liu, Ying Tai, Jilin Li, Shouhong Ding, Chengjie Wang, Feiyue Huang, Dongyang Li, Wenshuai Qi, Rongrong Ji
In this paper, we propose a light reflection based face anti-spoofing method named Aurora Guard (AG), which is fast, simple yet effective that has already been deployed in real-world systems serving for millions of users.
no code implementations • 31 Jul 2016 • Zhiwen Shao, Shouhong Ding, Yiru Zhao, Qinchuan Zhang, Lizhuang Ma
In this paper, we propose a novel face alignment method that trains deep convolutional network from coarse to fine.