Search Results for author: Xiangqun Chen

Found 8 papers, 3 papers with code

No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML

1 code implementation11 Oct 2023 Ziqi Zhang, Chen Gong, Yifeng Cai, Yuanyuan Yuan, Bingyan Liu, Ding Li, Yao Guo, Xiangqun Chen

These solutions, referred to as TEE-Shielded DNN Partition (TSDP), partition a DNN model into two parts, offloading the privacy-insensitive part to the GPU while shielding the privacy-sensitive part within the TEE.

Inference Attack Membership Inference Attack

DistFL: Distribution-aware Federated Learning for Mobile Scenarios

1 code implementation22 Oct 2021 Bingyan Liu, Yifeng Cai, Ziqi Zhang, Yuanchun Li, Leye Wang, Ding Li, Yao Guo, Xiangqun Chen

Previous studies focus on the "symptoms" directly, as they try to improve the accuracy or detect possible attacks by adding extra steps to conventional FL models.

Federated Learning Privacy Preserving

PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization

1 code implementation2 Mar 2021 Bingyan Liu, Yao Guo, Xiangqun Chen

Based on the grouping results, PFA conducts an FL process in a group-wise way on the federated model to accomplish the adaptation.

Federated Learning Privacy Preserving

TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning

no code implementations2 Mar 2021 Bingyan Liu, Yifeng Cai, Yao Guo, Xiangqun Chen

This paper aims to improve the transfer performance from another angle - in addition to tuning the weights, we tune the structure of pre-trained models, in order to better match the target task.

Transfer Learning

Adversarial Attacks on Monocular Depth Estimation

no code implementations23 Mar 2020 Ziqi Zhang, Xinge Zhu, Yingwei Li, Xiangqun Chen, Yao Guo

In order to understand the impact of adversarial attacks on depth estimation, we first define a taxonomy of different attack scenarios for depth estimation, including non-targeted attacks, targeted attacks and universal attacks.

Autonomous Driving Monocular Depth Estimation +3

Traffic Danger Recognition With Surveillance Cameras Without Training Data

no code implementations29 Nov 2018 Lijun Yu, Dawei Zhang, Xiangqun Chen, Alexander Hauptmann

Therefore, we developed a model to predict and identify car crashes from surveillance cameras based on a 3D reconstruction of the road plane and prediction of trajectories.

3D Reconstruction

MOBA-Slice: A Time Slice Based Evaluation Framework of Relative Advantage between Teams in MOBA Games

no code implementations22 Jul 2018 Lijun Yu, Dawei Zhang, Xiangqun Chen, Xing Xie

In this paper, we introduce MOBA-Slice, a time slice based evaluation framework of relative advantage between teams in MOBA games.

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