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New DOD-SA framework reduces annotation costs for infrared-visible object detection

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Researchers have developed a new framework called DOD-SA for infrared-visible object detection, which aims to reduce the high annotation costs associated with existing methods. This framework utilizes a Single- and Dual-Modality Collaborative Teacher-Student Network (CoSD-TSNet) to enable knowledge transfer between different modalities. The system employs a Progressive and Self-Tuning Training Strategy (PaST) and a Pseudo Label Assigner (PLA) to improve the accuracy of pseudo-labels and handle modality misalignment during training. AI

RANK_REASON The cluster contains a research paper detailing a new technical framework for object detection. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New DOD-SA framework reduces annotation costs for infrared-visible object detection

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The cluster contains a research paper detailing a new technical framework for object detection. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Hang Jin, Chenqiang Gao, Junjie Guo, Fangcen Liu, Qinyao Chang, Kanghui Tian, Deyu Meng ·

    DOD-SA: Infrared-Visible Decoupled Object Detection with Single-Modality Annotations

    arXiv:2508.10445v2 Announce Type: replace Abstract: Infrared-visible object detection has shown great potential in real-world applications, enabling robust all-day perception by leveraging the complementary information of infrared and visible images. However, existing methods typ…

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