WaveComm: Lightweight Communication for Collaborative Perception via Wavelet Feature Distillation

• URL: http://arxiv.org/abs/2603.13365v1
• Date: Mon, 09 Mar 2026 12:01:37 GMT
• Title: WaveComm: Lightweight Communication for Collaborative Perception via Wavelet Feature Distillation
• Abstract summary: WaveComm is a wavelet-based communication framework that drastically reduces transmission loads while preserving sensing performance in low-bandwidth scenarios.<n>The core innovation of WaveComm lies in decomposing feature maps using Discrete Wavelet Transform (DWT)<n> Experiments on the OPV2V and DAIR-V2X datasets for LiDAR-based and camera-based perception tasks demonstrate that WaveComm maintains state-of-the-art performance even when the communication volume is reduced to 86.3% and 87.0% of the original, respectively.
• Score: 7.524867292774759
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In multi-agent collaborative sensing systems, substantial communication overhead from information exchange significantly limits scalability and real-time performance, especially in bandwidth-constrained environments. This often results in degraded performance and reduced reliability. To address this challenge, we propose WaveComm, a wavelet-based communication framework that drastically reduces transmission loads while preserving sensing performance in low-bandwidth scenarios. The core innovation of WaveComm lies in decomposing feature maps using Discrete Wavelet Transform (DWT), transmitting only compact low-frequency components to minimize communication overhead. High-frequency details are omitted, and their effects are reconstructed at the receiver side using a lightweight generator. A Multi-Scale Distillation (MSD) Loss is employed to optimize the reconstruction quality across pixel, structural, semantic, and distributional levels. Experiments on the OPV2V and DAIR-V2X datasets for LiDAR-based and camera-based perception tasks demonstrate that WaveComm maintains state-of-the-art performance even when the communication volume is reduced to 86.3% and 87.0% of the original, respectively. Compared to existing approaches, WaveComm achieves competitive improvements in both communication efficiency and perception accuracy. Ablation studies further validate the effectiveness of its key components.

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