IEEE

A Flexible and Scalable Malicious Secure Aggregation Protocol for Federated Learning

Abstract: Secure aggregation becomes a major solution to providing privacy for federated learning. Secure aggregation for mobile devices typically relies on Shamir secret sharing (SSS) to achieve ...
IEEE

Domain Generalization via Aggregation and Separation for Audio Deepfake Detection

Abstract: In this paper, we propose an Aggregation and Separation Domain Generalization (ASDG) method for Audio DeepFake Detection (ADD). Fake speech generated from different methods exhibits varied ...
IEEE

An Aggregation-Free Federated Learning for Tackling Data Heterogeneity

Abstract: The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an aggregate-then-adapt framework, where ...
IEEE

Dual Aggregation Transformer for Image Super-Resolution

Abstract: Transformer has recently gained considerable popularity in low-level vision tasks, including image super-resolution (SR). These networks utilize self-attention along different dimensions, ...
IEEE

Multistage Particle Swarm Optimization for Heterogeneous Multipoint Dynamic Aggregation

Abstract: Multipoint dynamic aggregation (MPDA) is a multirobot task allocation problem, which requires the collaborative scheduling of multiple robots to complete time-varying tasks distributed on a ...
IEEE

FedAWA: Aggregation Weight Adjustment in Federated Domain Generalization

Abstract: Domain Generalization (DG) in the setting of federated learning (i.e. Federated Domain Generalization, FDG) is gaining increasing attention. FDG aims to learn a global model generalizing ...
IEEE

Cross-Modality Feature Aggregation for Cross-Domain Point Cloud Representation Learning

Abstract: Existing methods for learning 3D point cloud representation often use a single dataset-specific training and testing approach, leading to performance drops due to significant domain shifts ...
IEEE

3D point cloud robust sampling method based on aggregation rate

Abstract: Effective sampling plays a critical role in the preprocessing of 3D point cloud data, directly impacting the performance of downstream models. Traditional Farthest Point Sampling (FPS) ...
IEEE

Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection

Abstract: In this work, we propose a novel method termed Frustum ConvNet (F-ConvNet) for amodal 3D object detection from point clouds. Given 2D region proposals in an RGB image, our method first ...