39 / 2023-08-29 17:19:21
A Data Augmentation Method Based on Multi-Modal Image Fusion for Detection and Segmentation
object detection,semantic segmentation,data augmentation,image fusion
终稿
Jing Zhang / University of Science and Technology of China
Gang Yang / University of Science and Technology of China
Aiping Liu / University of Science and Technology of China
Xun Chen / University of Science and Technology of China
In the field of computer vision, effective data augmentation plays a crucial role in enhancing the robustness and generalization capability of visual models. This paper proposes a novel data augmentation method based on multi-modal image fusion. Unlike traditional augmentation approaches, the proposed method focuses on synthesizing the fused samples that contain complementary scene characteristics from different modalities while actively suppressing useless and redundant information. To evaluate the effectiveness of our method, the experiments were conducted in the contexts of both object detection and semantic segmentation. The experimental results demonstrate that our method can significantly improve the accuracy of visual models than original samples.
重要日期
  • 会议日期

    11月02日

    2023

    11月04日

    2023

  • 12月15日 2023

    初稿截稿日期

  • 12月20日 2023

    注册截止日期

主办单位
IEEE Instrumentation and Measurement Society
Xidian University
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