Weiming Zhuang

papers

303

total citations

papers (11)

Collaborative Unsupervised Visual Representation Learning From Decentralized Data

ICCV 2021arXiv

117

citations

A Simple Background Augmentation Method for Object Detection with Diffusion Model

ECCV 2024arXiv

citations

Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators

AAAI 2024arXiv

citations

COALA: A Practical and Vision-Centric Federated Learning Platform

ICML 2024arXiv

citations

Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety

CVPR 2025

citations

Argus: A Compact and Versatile Foundation Model for Vision

CVPR 2025

citations

MixA: A Mixed Attention approach with Stable Lightweight Linear Attention to enhance Efficiency of Vision Transformers at the Edge

ICCV 2025

citations

Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning

NEURIPS 2023

citations

Weiming Zhuang

papers (11)

Collaborative Unsupervised Visual Representation Learning From Decentralized Data

TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation

MAS: Towards Resource-Efficient Federated Multiple-Task Learning

FedMef: Towards Memory-efficient Federated Dynamic Pruning

A Simple Background Augmentation Method for Object Detection with Diffusion Model

Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators

COALA: A Practical and Vision-Centric Federated Learning Platform

Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety

Argus: A Compact and Versatile Foundation Model for Vision

MixA: A Mixed Attention approach with Stable Lightweight Linear Attention to enhance Efficiency of Vision Transformers at the Edge

Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning

papers (11)

Collaborative Unsupervised Visual Representation Learning From Decentralized Data

TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation

MAS: Towards Resource-Efficient Federated Multiple-Task Learning

FedMef: Towards Memory-efficient Federated Dynamic Pruning

A Simple Background Augmentation Method for Object Detection with Diffusion Model

Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators

COALA: A Practical and Vision-Centric Federated Learning Platform

Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety

Argus: A Compact and Versatile Foundation Model for Vision

MixA: A Mixed Attention approach with Stable Lightweight Linear Attention to enhance Efficiency of Vision Transformers at the Edge

Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning