9 citations · 39 across the 14 of their papers we have counts for
14 papers
Robust Estimation of Sparse Numerical Vectors under Local Differential Privacy
Puning Zhao, Zhikun Zhang, Shaowei Wang +5
Local differential privacy (LDP) protocols are vulnerable to poisoning attacks. Existing research have proposed efficient defense strategies for single-item users. However, in prac…
Generalized Semantic Contrastive Learning via Embedding Side Information for Few-Shot Object Detection
Ruoyu Chen, Hua Zhang, Jingzhi Li +3
The objective of few-shot object detection (FSOD) is to detect novel objects with few training samples. The core challenge of this task is how to construct a generalized feature sp…
Dynamic Analysis and Adaptive Discriminator for Fake News Detection
Xinqi Su, Zitong Yu, Yawen Cui +7
In current web environment, fake news spreads rapidly across online social networks, posing serious threats to society. Existing multimodal fake news detection methods can generall…
GVformer: Graph Guided Video Vision Transformer for Face Anti-Spoofing
Jingyi Yang, Zitong Yu, Xiuming Ni +2
In videos containing spoofed faces, we may uncover the spoofing evidence based on either photometric or dynamic abnormality, even a combination of both. Prevailing face anti-spoofi…
Hierarchical Invariance for Robust and Interpretable Vision Tasks at Larger Scales
Shuren Qi, Yushu Zhang, Chao Wang +3
Developing robust and interpretable vision systems is a crucial step towards trustworthy artificial intelligence. In this regard, a promising paradigm considers embedding task-requ…
Asymmetrically Decentralized Federated Learning
Qinglun Li, Miao Zhang, Nan Yin +2
To address the communication burden and privacy concerns associated with the centralized server in Federated Learning (FL), Decentralized Federated Learning (DFL) has emerged, whic…
Content-Aware Quantization Index Modulation:Leveraging Data Statistics for Enhanced Image Watermarking
Junlong Mao, Huiyi Tang, Shanxiang Lyu +2
Image watermarking techniques have continuously evolved to address new challenges and incorporate advanced features. The advent of data-driven approaches has enabled the processing…
Reversible Quantization Index Modulation for Static Deep Neural Network Watermarking
Junren Qin, Shanxiang Lyu, Fan Yang +3
Static deep neural network (DNN) watermarking techniques typically employ irreversible methods to embed watermarks into the DNN model weights. However, this approach causes permane…
FedSOV: Federated Model Secure Ownership Verification with Unforgeable Signature
Wenyuan Yang, Gongxi Zhu, Yuguo Yin +4
Federated learning allows multiple parties to collaborate in learning a global model without revealing private data. The high cost of training and the significant value of the glob…
FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof
Wenyuan Yang, Yuguo Yin, Gongxi Zhu +4
Federated learning (FL) allows multiple parties to cooperatively learn a federated model without sharing private data with each other. The need of protecting such federated models…
Spatial-Frequency Discriminability for Revealing Adversarial Perturbations
Chao Wang, Shuren Qi, Zhiqiu Huang +4
The vulnerability of deep neural networks to adversarial perturbations has been widely perceived in the computer vision community. From a security perspective, it poses a critical…
Visual Content Privacy Protection: A Survey
Ruoyu Zhao, Yushu Zhang, Tao Wang +3
Vision is the most important sense for people, and it is also one of the main ways of cognition. As a result, people tend to utilize visual content to capture and share their life…
Representing Noisy Image Without Denoising
Shuren Qi, Yushu Zhang, Chao Wang +3
A long-standing topic in artificial intelligence is the effective recognition of patterns from noisy images. In this regard, the recent data-driven paradigm considers 1) improving…
Adaptive 3D Mesh Steganography Based on Feature-Preserving Distortion
Yushu Zhang, Jiahao Zhu, Mignfu Xue +2
Current 3D mesh steganography algorithms relying on geometric modification are prone to detection by steganalyzers. In traditional steganography, adaptive steganography has proven…