Transactions of Nanjing University of Aeronautics & Astronautics
DeHCP: A Decoupled Framework for Scalable Open Heterogeneous Collaborative Perception
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Abstract:
The existing open heterogeneous collaborative perception systems typically align diverse features to a fixed semantic space. This alignment process inevitably leads to information loss and suppresses modality-specific characteristics. To address this limitation， this paper introduces a novel decoupled heterogeneous collaborative perception （DeHCP） framework， which decouples the intermediate feature space into a shared branch and a specific branch. The shared branch extracts a modality-agnostic common representation， while the specific branch preserves modality-specific characteristics conditioned on learnable modality embeddings. A dynamic gate aggregation mechanism adaptively integrates these specific features with the common representation， based on the global semantic context and ego-agent identity. Furthermore， a decoupled supervision strategy with backward alignment enables the integration of unseen heterogeneous agents by updating only local encoders and lightweight adapters， thereby avoiding collective retraining. Extensive experiments on collaborative benchmarks demonstrate that DeHCP achieves improved three-dimensional object detection accuracy while maintaining the extensibility of open heterogeneous collaborative perception through backward alignment. The proposed approach supports the development of highly scalable autonomous driving systems. Code is available at Keywords:
Project Supported:
This work was supported by the National Key Research and Development Program of China（No.2025ZD0124204）， the National Natural Science Foundation of China（No.U24A20252）， the Fundamental and Interdisciplinary Disciplines Breakthrough Plan of the Ministry of Education of China （No.JYB2025XDXM504）， the Fuzhou Artificial Intelligence“List-Bidding & Task-Commissioning”Project（No.2025-ZD-038）， the Natural Science Basic Research Plan in Shaanxi Province of China （No.2026JC-YBQN-0779）， and the Fundamental Research Fund for the Central Universities（No.xzy012026035）.
Clc Number:
TP391.4
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