Zhiqin Zhu — accepted AI-conference papers

2026

Customized Fusion: A Closed-Loop Dynamic Network for Adaptive Multi-Task-Aware Infrared-Visible Image Fusion

Zengyi Yang, Yu Liu, Juan Cheng, Zhiqin Zhu, Yafei Zhang, Huafeng Li

CVPR 2026

Infrared-visible image fusion aims to integrate complementary information for robust visual understanding, but existing fusion methods struggle with simultaneously adapting to multiple downstream tasks. To address this issue, we propose a Closed-Loop Dynamic Network (CLDyN) that can adaptively respo

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2025

Transforming Gaps into Gains: Bridging Model and Data Heterogeneity in Federated Learning via Knowledge Weak-Aware Zones

Ke Li, Yan Ding, Zhiqin Zhu, Shenhai Zheng

NeurIPS 2025poster

Heterogeneous federated learning enables collaborative training across clients under dual heterogeneity of models and data, posing challenges for effective knowledge transfer. Federated mutual learning employs proxy models to bridge cross-model knowledge exchange; however, existing methods remain li…

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