Challenges
This year, we are running the following challenges:
- Hierarchical Panoptic Segmentation of Crops and Weeds
- Deep Nutrient Deficiency - Dikopshof - Winter Wheat and Winter Rye
There will be a part of the workshop, where we announce the winners and plan to award a certificate for winning entries that provide a short description of their technical approach by a short technical report.
Please feel free to participate to these challenges and submit your solutions as an extended abstract or full paper. Visit the Call for Papers page for further details. Valerio Giuffrida is the challenges lead; contact with questions or concerns. Please also contact the competition organizers with specific questions regarding the competition.
Hierarchical Panoptic Segmentation of Crops and Weeds
In this challenge, one has to provide a hierarchical panoptic segmentation of sugar beets and weeds. More specifically, methods have to predict a semantic segmentation of sugar beets and weeds, but also an instance segmentation of crops and instance segmentation of the leaves. Thus, it is possible to get phenotypic information of the whole crop but also more fine-grained information.
More details about this challenge can be found here.
Please contact Jens Behley if you have specific questions about this competition and concerns regarding the submission on CodaLab.
The challenge concluded on September 1, 2023 and the ranking of the competition have been determined based on the score and the submitted technical report.
| Place | Authors | Technical Report |
| 1 | Lu et al., Xidian University, China | |
| 2 | Nguyen et al., National Yang Ming Chiao Tung University, Taiwan | |
| 3 | Güldenring et al., Technical University of Denmark, Denmark | |
| 4 | Chen et al., University of Science and Technology of China, China | |
| 5 | Darbyshire et al., University of Lincoln, UK |
Note: The technical reports (up to 4 pages) are non-peer reviewed descriptions of the technical approach of the submissions. All contents are the intellectual property of the respective authors and should be acknowledged accordingly.
The 1st, 2nd, and 3rd place get a certificate and have the opportunity to present their work at the workshop.
Deep Nutrient Deficiency - Dikopshof - Winter Wheat and Winter Rye
In this challenge, we provide an image dataset of winter wheat and winter rye, where the task is to perform image classification to determine fertilizer treatments and consequently a solution to recognize nutrient deficiencies.
More details about the challenge can be found here.
Please contact Jinhui Yi if you have specific questions about this competition and concerns regarding the submission on CodaLab.
The challenge concluded on September 1, 2023 and the ranking of the competition have been determined based on the score and the submitted technical report.
| Place | Authors | Technical Report |
| 1 | Zhang et al., University of Queensland, Australia | |
| 2 | Wang et al., Technical University of Munich, Germany | |
| 3 | Liu et al., Xi’an Jiaotong University, China | |
| 4 | Kuzu et al., Germany Aerospace Center (DLR), Germany |
Note: The technical reports (up to 4 pages) are non-peer reviewed descriptions of the technical approach of the submissions. All contents are the intellectual property of the respective authors and should be acknowledged accordingly.
The 1st, 2nd, and 3rd place get a certificate and have the opportunity to present their work at the workshop.