mlsanityData to 14 Oct 2026

DooDLeNet: Double DeepLab Enhanced Feature Fusion for Thermal-color Semantic Segmentation

arXiv 2204.10266 ↗First posted 21 Apr 2022cs.LG cs.CV eess.IVcited by 13

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Abstract (arXiv)

In this paper we present a new approach for feature fusion between RGB and LWIR Thermal images for the task of semantic segmentation for driving perception. We propose DooDLeNet, a double DeepLab architecture with specialized encoder-decoders for thermal and color modalities and a shared decoder for final segmentation. We combine two strategies for feature fusion: confidence weighting and correlation weighting. We report state-of-the-art mean IoU results on the MF dataset.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 21 of its 30 references that are in the map. First posted on arXiv 21 Apr 2022.

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21 of 30 references.

References · 21

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9 more
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Citing papers per year: 2023: 4; 2024: 4; 2025: 2; 2026: 3.

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