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New AVID dataset targets drone detection with RGB-Infrared imagery

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced AVID, a new dataset and benchmark designed for the detection of small aerial targets, particularly drones, using combined RGB and infrared imagery. The dataset, comprising over 32,000 frame pairs, focuses on targets that are unusually small, with most occupying only 8-16 pixels. AVID also includes a perturbation benchmark, AVID-C, which simulates various image degradations to assess how these factors, along with cross-modal alignment challenges, impact detection performance. The findings suggest that combining RGB and infrared data significantly improves detection accuracy for these tiny targets compared to using either modality alone. AI

IMPACT This dataset could advance research in small object detection and sensor fusion for surveillance applications.

RANK_REASON The item is a research paper detailing a new dataset and benchmark for computer vision tasks. [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 AVID dataset targets drone detection with RGB-Infrared imagery

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The item is a research paper detailing a new dataset and benchmark for computer vision tasks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Dharini Raghavan, Vishnu Rao, Sethu Selvi S ·

    AVID: A Weakly Aligned RGB-Infrared Dataset and Perturbation Benchmark for Tiny Aerial Targets

    arXiv:2610.40949v1 Announce Type: new Abstract: Long-range detection of small drones is complicated by their visual similarity to birds and by the limited detail available from ground-based cameras. Combining visible and infrared observations offers complementary information, but…

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