99 citations · 635 across the 57 of their papers we have counts for
17 papers · 1 filter
Artificial Intelligence Security Competition (AISC)
Yinpeng Dong, Peng Chen, Senyou Deng +49
The security of artificial intelligence (AI) is an important research area towards safe, reliable, and trustworthy AI systems. To accelerate the research on AI security, the Artifi…
Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition
Shuai Jia, Bangjie Yin, Taiping Yao +4
Deep learning models have shown their vulnerability when dealing with adversarial attacks. Existing attacks almost perform on low-level instances, such as pixels and super-pixels,…
SoccerNet 2022 Challenges Results
Silvio Giancola, Anthony Cioppa, Adrien Deliège +91
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks:…
Towards Stable Co-saliency Detection and Object Co-segmentation
Bo Li, Lv Tang, Senyun Kuang +2
In this paper, we present a novel model for simultaneous stable co-saliency detection (CoSOD) and object co-segmentation (CoSEG). To detect co-saliency (segmentation) accurately, t…
Adma-GAN: Attribute-Driven Memory Augmented GANs for Text-to-Image Generation
Xintian Wu, Hanbin Zhao, Liangli Zheng +2
As a challenging task, text-to-image generation aims to generate photo-realistic and semantically consistent images according to the given text descriptions. Existing methods mainl…
ECO-TR: Efficient Correspondences Finding Via Coarse-to-Fine Refinement
Dongli Tan, Jiang-Jiang Liu, Xingyu Chen +5
Modeling sparse and dense image matching within a unified functional correspondence model has recently attracted increasing research interest. However, existing efforts mainly focu…
Federated Learning with Label Distribution Skew via Logits Calibration
Jie Zhang, Zhiqi Li, Bo Li +4
Traditional federated optimization methods perform poorly with heterogeneous data (ie, accuracy reduction), especially for highly skewed data. In this paper, we investigate the lab…
Domain Adaptive Person Search
Junjie Li, Yichao Yan, Guanshuo Wang +3
Person search is a challenging task which aims to achieve joint pedestrian detection and person re-identification (ReID). Previous works have made significant advances under fully…
Adaptive Mixture of Experts Learning for Generalizable Face Anti-Spoofing
Qianyu Zhou, Ke-Yue Zhang, Taiping Yao +3
With various face presentation attacks emerging continually, face anti-spoofing (FAS) approaches based on domain generalization (DG) have drawn growing attention. Existing DG-based…
Privacy-Preserving Face Recognition with Learnable Privacy Budgets in Frequency Domain
Jiazhen Ji, Huan Wang, Yuge Huang +6
Face recognition technology has been used in many fields due to its high recognition accuracy, including the face unlocking of mobile devices, community access control systems, and…
DuetFace: Collaborative Privacy-Preserving Face Recognition via Channel Splitting in the Frequency Domain
Yuxi Mi, Yuge Huang, Jiazhen Ji +4
With the wide application of face recognition systems, there is rising concern that original face images could be exposed to malicious intents and consequently cause personal priva…
Generative Domain Adaptation for Face Anti-Spoofing
Qianyu Zhou, Ke-Yue Zhang, Taiping Yao +4
Face anti-spoofing (FAS) approaches based on unsupervised domain adaption (UDA) have drawn growing attention due to promising performances for target scenarios. Most existing UDA F…
Evaluation-oriented Knowledge Distillation for Deep Face Recognition
Yuge Huang, Jiaxiang Wu, Xingkun Xu +1
Knowledge distillation (KD) is a widely-used technique that utilizes large networks to improve the performance of compact models. Previous KD approaches usually aim to guide the st…
Geometric Synthesis: A Free lunch for Large-scale Palmprint Recognition Model Pretraining
Kai Zhao, Lei Shen, Yingyi Zhang +6
Palmprints are private and stable information for biometric recognition. In the deep learning era, the development of palmprint recognition is limited by the lack of sufficient tra…
Exploring Frequency Adversarial Attacks for Face Forgery Detection
Shuai Jia, Chao Ma, Taiping Yao +3
Various facial manipulation techniques have drawn serious public concerns in morality, security, and privacy. Although existing face forgery classifiers achieve promising performan…
ContrastMask: Contrastive Learning to Segment Every Thing
Xuehui Wang, Kai Zhao, Ruixin Zhang +3
Partially-supervised instance segmentation is a task which requests segmenting objects from novel unseen categories via learning on limited seen categories with annotated masks thu…
Towards Practical Certifiable Patch Defense with Vision Transformer
Zhaoyu Chen, Bo Li, Jianghe Xu +3
Patch attacks, one of the most threatening forms of physical attack in adversarial examples, can lead networks to induce misclassification by modifying pixels arbitrarily in a cont…