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New pipeline automates low-light pedestrian detection labeling

By PulseAugur Editorial · [1 sources] ·

Researchers have developed an automated pipeline to generate labels for low-light pedestrian detection using infrared and RGB cameras. This method involves detecting pedestrians in infrared images and then transferring those labels to corresponding RGB images. Models trained with these generated labels outperformed those trained on ground truth in several key metrics, suggesting a scalable approach for creating large low-light pedestrian datasets. AI

IMPACT Automated labeling could accelerate the development of safer autonomous driving systems by improving low-light pedestrian detection.

RANK_REASON The cluster contains an academic paper detailing a new methodology 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 pipeline automates low-light pedestrian detection labeling

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The cluster contains an academic paper detailing a new methodology 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) · Dimitrios Bouzoulas, Eerik Alamikkotervo, Risto Ojala ·

    Automatic Labelling for Low-Light Pedestrian Detection

    arXiv:2507.02513v4 Announce Type: replace Abstract: Pedestrian detection in RGB images is a key task in pedestrian safety, as the most common sensor in autonomous vehicles and advanced driver assistance systems is the RGB camera. Low-light pedestrian detection lacks large public …

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