ABCDWaveNet: Advancing Robust Road Ponding Detection in Fog through Dynamic Frequency-Spatial Synergy Article Swipe

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Ronghui Zhang , Ding Lyu , Tengfei Li , Ujjal Manandhar , Bolin Gao , Danwei Wang ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2504.05112

Road ponding presents a significant threat to vehicle safety, particularly in adverse fog conditions, where reliable detection remains a persistent challenge for Advanced Driver Assistance Systems (ADAS). To address this, we propose ABCDWaveNet, a novel deep learning framework leveraging Dynamic Frequency-Spatial Synergy for robust ponding detection in fog. The core of ABCDWaveNet achieves this synergy by integrating dynamic convolution for adaptive feature extraction across varying visibilities with a wavelet-based module for synergistic frequency-spatial feature enhancement, significantly improving robustness against fog interference. Building on this foundation, ABCDWaveNet captures multi-scale structural and contextual information, subsequently employing an Adaptive Attention Coupling Gate (AACG) to adaptively fuse global and local features for enhanced accuracy. To facilitate realistic evaluations under combined adverse conditions, we introduce the Foggy Low-Light Puddle dataset. Extensive experiments demonstrate that ABCDWaveNet establishes new state-of-the-art performance, achieving significant Intersection over Union (IoU) gains of 3.51%, 1.75%, and 1.03% on the Foggy-Puddle, Puddle-1000, and our Foggy Low-Light Puddle datasets, respectively. Furthermore, its processing speed of 25.48 FPS on an NVIDIA Jetson AGX Orin confirms its suitability for ADAS deployment. These findings underscore the effectiveness of the proposed Dynamic Frequency-Spatial Synergy within ABCDWaveNet, offering valuable insights for developing proactive road safety solutions capable of operating reliably in challenging weather conditions.

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2504.05112
PDF: https://arxiv.org/pdf/2504.05112
OA Status: green
OpenAlex ID: https://openalex.org/W4416118513

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OpenAlex ID: https://openalex.org/W4416118513

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DOI: https://doi.org/10.48550/arxiv.2504.05112

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Title: ABCDWaveNet: Advancing Robust Road Ponding Detection in Fog through Dynamic Frequency-Spatial Synergy

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-04-07

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Authors: Ronghui Zhang, Ding Lyu, Tengfei Li, Ujjal Manandhar, Bolin Gao, Danwei Wang

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Landing page: https://arxiv.org/abs/2504.05112

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PDF URL: https://arxiv.org/pdf/2504.05112

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OA URL: https://arxiv.org/pdf/2504.05112

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Cited by: 0

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