mlsanityData to 14 Oct 2026

Pedestrain detection for low-light vision proposal

arXiv 2303.12725 ↗First posted 17 Mar 2023cs.CV cs.AIcited by 0

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Abstract (arXiv)

The demand for pedestrian detection has created a challenging problem for various visual tasks such as image fusion. As infrared images can capture thermal radiation information, image fusion between infrared and visible images could significantly improve target detection under environmental limitations. In our project, we would approach by preprocessing our dataset with image fusion technique, then using Vision Transformer model to detect pedestrians from the fused images. During the evaluation procedure, a comparison would be made between YOLOv5 and the revised ViT model performance on our fused images

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 24 references that are in the map. First posted on arXiv 17 Mar 2023.

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3 of 24 references.

References · 3

  1. 2021LLVIP: A Visible-infrared Paired Dataset for Low-light Visioncited by 231
  2. 2018DenseFuse: A Fusion Approach to Infrared and Visible Imagescited by 180
  3. 2020Improved Actor Relation Graph based Group Activity Recognitioncited by 2

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