Agriculture-Vision Challenge 2022 -- The Runner-Up Solution for Agricultural Pattern Recognition via Transformer-based Models

Zhicheng Yang; Jui-Hsin Lai; Jun Zhou; Hang Zhou; Chen Du; Zhongcheng Lai

Agriculture-Vision Challenge 2022 -- The Runner-Up Solution for Agricultural Pattern Recognition via Transformer-based Models

Computer Vision and Pattern Recognition 2022-06-27 v1

Authors: Zhicheng Yang , Jui-Hsin Lai , Jun Zhou , Hang Zhou , Chen Du , Zhongcheng Lai

Abstract

The Agriculture-Vision Challenge in CVPR is one of the most famous and competitive challenges for global researchers to break the boundary between computer vision and agriculture sectors, aiming at agricultural pattern recognition from aerial images. In this paper, we propose our solution to the third Agriculture-Vision Challenge in CVPR 2022. We leverage a data pre-processing scheme and several Transformer-based models as well as data augmentation techniques to achieve a mIoU of 0.582, accomplishing the 2nd place in this challenge.

Keywords

agricultural pattern recognition transformer data augmentation semantic segmentation aerial images agriculture-vision challenge

Cite

@article{arxiv.2206.11920,
  title  = {Agriculture-Vision Challenge 2022 -- The Runner-Up Solution for Agricultural Pattern Recognition via Transformer-based Models},
  author = {Zhicheng Yang and Jui-Hsin Lai and Jun Zhou and Hang Zhou and Chen Du and Zhongcheng Lai},
  journal= {arXiv preprint arXiv:2206.11920},
  year   = {2022}
}

Comments

CVPR 2022, Agriculture-Vision Challenge, Remote Sensing

Agriculture-Vision Challenge 2022 -- The Runner-Up Solution for Agricultural Pattern Recognition via Transformer-based Models

Abstract

Keywords

Cite

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