Log In Sign Up

Global Wheat Head Dataset 2021: an update to improve the benchmarking wheat head localization with more diversity

by   Etienne David, et al.

The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4,700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD has successfully attracted attention from both the computer vision and agricultural science communities. From this first experience in 2020, a few avenues for improvements have been identified, especially from the perspective of data size, head diversity and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and augmented by adding 1,722 images from 5 additional countries, allowing for 81,553 additional wheat heads to be added. We would hence like to release a new version of the Global Wheat Head Detection (GWHD) dataset in 2021, which is bigger, more diverse, and less noisy than the 2020 version. The GWHD 2021 is now publicly available at and a new data challenge has been organized on AIcrowd to make use of this updated dataset.


page 2

page 3

page 5


Global Wheat Challenge 2020: Analysis of the competition design and winning models

Data competitions have become a popular approach to crowdsource new data...

Detecting Heads using Feature Refine Net and Cascaded Multi-scale Architecture

This paper presents a method that can accurately detect heads especially...

Analysis of Self-Attention Head Diversity for Conformer-based Automatic Speech Recognition

Attention layers are an integral part of modern end-to-end automatic spe...

Head Detection with Depth Images in the Wild

Head detection and localization is a demanding task and a key element fo...