Pedestrain detection for low-light vision proposal

• URL: http://arxiv.org/abs/2303.12725v1
• Date: Fri, 17 Mar 2023 04:13:58 GMT
• Title: Pedestrain detection for low-light vision proposal
• Authors: Zhipeng Chang, Ruiling Ma, Wenliang Jia
• Abstract summary: The demand for pedestrian detection has created a challenging problem for various visual tasks such as image fusion. 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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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

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