🔦 Rules
To participate, you have to agree to the following rules:
- As we can’t allow access to the test images during the competition, the final model and code must be submitted in a docker container. You will be given a template docker container to use for this.
- Participants are requested to publish a (brief) description of their method and results on ArXiv (or similar pre-print platforms) that is linked to their final submission. There is no page limit for that description, but it has to include a conclusive description of the approach of the participating team.
- Training data is licensed as CC BY, i.e. everyone (also non-participants of the challenge) are free to use the training data set in their respective work, given attribution in the publication.
- For
participation in award category 1, participants are allowed to use all publicly available data for training and select any network architecture.
- For participation in award category 2 (data-centric challenge), participants are not allowed to use any additional (publicly available) data, and the reference network implementation must be used. However, it is permitted to use AI models in the data pipeline under the following conditions:
- the AI models ONLY alter/augment the data or synthetically generate new data but they don’t generate the prediction;
- the AI models can be pretrained but have to be as such publicly available, but it is NOT allowed to train them on any ADDITIONAL data (only the challenge dataset is allowed for training).
- We added this clarification to our challenge rules: https://autopet-iii.grand-challenge.org/rules/
- Algorithms
must be made publicly available as e.g. GitHub repository with a
permissive open source license (Apache Licence 2.0, MIT Licence, GNU GPLv3, GNU AGPLv3, Mozilla Public Licence 2.0, Boost Software Licence 1.0, The Unlicence)
- To avoid potential conflicts of interest, researchers affiliated with the institutes of the organizers are not allowed to participate.
- The provided baselines will hold their respective positions but without eligibility for prize money.
- Resubmissions of the provided baseline model in award category 1 are not eligible for prizes.
Publication policy
- Participants may publish papers including their official performance on the challenge data set, given proper reference of the challenge and the dataset. There is no embargo time in that regard. Please use the following references:Database:
, TBA
Challenge: TBA - We aim to publish a summary of the challenge in a peer-reviewed journal (further information). The first and last author of the submitted arxiv paper will qualify as authors in the summary paper. Participating teams are free to publish their own results in a separate publication after coordination with the authors of the challenge to avoid significant overlap with the summary paper.