Agriculture-Vision Challenge 2022 -- The Runner-Up Solution for Agricultural Pattern Recognition via Transformer-based Models
This work addresses agricultural pattern recognition for researchers and practitioners in computer vision and agriculture, but it is incremental as it builds on existing Transformer-based methods for a specific challenge.
The paper tackled agricultural pattern recognition from aerial images in the Agriculture-Vision Challenge 2022, achieving second place with a mean Intersection over Union (mIoU) score of 0.582 using data pre-processing, Transformer-based models, and data augmentation techniques.
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.