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
Final Paper
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.
Important Date
  • Conference Date

    Nov 02

    2023

    to

    Nov 04

    2023

  • Dec 15 2023

    Draft paper submission deadline

  • Dec 20 2023

    Registration deadline

Sponsored By
IEEE Instrumentation and Measurement Society
Xidian University