Papers › Complementary Random Masking for RGB-Thermal Semantic Segmentation

Complementary Random Masking for RGB-Thermal Semantic Segmentation

30 Mar 2023arXiv:2303.17386archive 2025-07-28

Ukcheol Shin, Kyunghyun Lee, In So Kweon, Jean Oh

RGB-thermal semantic segmentation is one potential solution to achieve reliable semantic scene understanding in adverse weather and lighting conditions. However, the previous studies mostly focus on designing a multi-modal fusion module without consideration of the nature of multi-modality inputs. Therefore, the networks easily become over-reliant on a single modality, making it difficult to learn complementary and meaningful representations for each modality. This paper proposes 1) a complementary random masking strategy of RGB-T images and 2) self-distillation loss between clean and masked input modalities. The proposed masking strategy prevents over-reliance on a single modality. It also improves the accuracy and robustness of the neural network by forcing the network to segment and classify objects even when one modality is partially available. Also, the proposed self-distillation loss encourages the network to extract complementary and meaningful representations from a single modality or complementary masked modalities. Based on the proposed method, we achieve state-of-the-art performance over three RGB-T semantic segmentation benchmarks. Our source code is available at https://github.com/UkcheolShin/CRM_RGBTSeg.

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batch_dice_loss UkcheolShin/CRM_RGBTSeg/models/mask2former/matcher.py official repository unverified MIT (permissive) · bc2cb481a75c370d · report
batch_sigmoid_ce_loss UkcheolShin/CRM_RGBTSeg/models/mask2former/matcher.py official repository unverified MIT (permissive) · 1edd24985036b0bf · report
calculate_uncertainty UkcheolShin/CRM_RGBTSeg/models/mask2former/criterion.py official repository unverified MIT (permissive) · 2dcb8123d89bb1ff · report
dice_loss UkcheolShin/CRM_RGBTSeg/models/mask2former/criterion.py official repository unverified MIT (permissive) · 89f75e54ff128be0 · report
sigmoid_ce_loss UkcheolShin/CRM_RGBTSeg/models/mask2former/criterion.py official repository unverified MIT (permissive) · d0c61e8dba511aa3 · report

Tasks

Scene UnderstandingSemantic SegmentationThermal Image Segmentation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Thermal Image Segmentation KP day-night CRM_RGBTSeg mIoU 55.2 #2 of 5 Archive leaderboard report
Thermal Image Segmentation MFN Dataset CRM_RGBT_Seg mIOU 61.4 #3 of 55 Archive leaderboard report
Thermal Image Segmentation PST900 CRM_RGBTSeg mIoU 88 #3 of 22 Archive leaderboard report

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