Aug 2026· Italian National Conference on Sensors· Vol 26, pp. 5517· 0 citations· 27 references
Medicine
TL;DR
The results indicate that compact cross-modal interaction can strengthen visible–infrared UAV detection while keeping computational costs moderate.
Abstract
Visible–infrared small-target detection is challenged by weak single-modality representation, modality discrepancy, and the quadratic cost of dense cross-modal attention. We propose TFFB, a feature-level fusion detector that combines spatial feature compression (SFC), cross-attention modality enhancement (CME), and iterative cross-modal enhancement (ICME) to balance information exchange and computational efficiency. To further improve localization, we introduce Focaler-SIoU for small-box regression. On Anti-UAV300, TFFB improves the middle-fusion baseline from 76.2%/43.7% to 81.5%/48.6% in mAP@0.5/mAP@0.5:0.95, and TFFB with Focaler-SIoU reaches 83.6% and 50.2%, respectively. The results indicate that compact cross-modal interaction can strengthen visible–infrared UAV detection while keeping computational costs moderate.
Object detection in complex lighting and harsh environments significantly benefits from the synergistic deployment of visible and infrared spectra. However, most existing dual-modality methods follow a two-stage pipeline termed ‘fusion-then-detection’, inevitably entailing substantial model complexity and intensive com...
Chao Zeng, Hao Zhao, Ju Zhou· Measurement science and tech...· 0 citations
Small-object detection under low illumination remains a persistent challenge in aerial surveillance, nighttime patrol, and safety-critical vision tasks, where single-modality sensors—RGB or infrared alone—provide degraded or incomplete target information. This paper proposes an RGB-T object detection network that combi...
A Lighting-Aware Spatial–Frequency Fusion Network (LASFNet) for security surveillance, which balances target saliency and scene structure, providing more effective visual input for object detection under complex illumination.
Yi Jiang, Xin Nie, Imad Rida· Algorithms· 0 citations
Infrared small-target detection is widely used in early warning and remote monitoring. The targets are usually extremely weak, extremely small, and easily obscured by the chaotic background. However, existing methods still have poor detection accuracy in low-contrast and highly interfering scenarios, and many methods r...
Hao-Zhe Wang, Si-Bao Chen· Journal of Physics, Conferen...· 0 citations
Object detection using visible–infrared images has become increasingly important for all-day detection scenarios. However, due to significant imaging discrepancies between the visible and infrared modalities, achieving accurate modal alignment and effective feature fusion remains a major challenge. Existing methods oft...
Kai-Yue Men, Cheng-You Wang, Xiao Zhou et al.· IEEE Transactions on Geoscie...· 0 citations
This paper proposes TDSF-Net, a target-driven sparse fusion network for real-time RGB-infrared weak small object detection, which follows an enhance-then-fuse paradigm and achieves state-of-the-art performance on the UAV-based DroneVehicle dataset.
Jian-Yuan Wang, Lang Liu, Jin-Bao Chen et al.· Journal of Real-Time Image P...· 0 citations
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