ImageCLEF 2020 VQA-Med - VQG
Note: ImageCLEF 2020 VQA-Med includes 2 tasks. This page is about the Visual Question Generation (VQG) task. For information about the Visual Question Answering task (VQA) click here. Both challenges share the same dataset, so registering for one of these challenges will automatically give you access to the other one.
Note: ImageCLEF 2020 VQA-Med is part of the official ImageCLEF 2020 medical task. Here is a list of other ImageCLEF 2020 medical task challenges:
Note: Please do not forget to read the Rules section on this page. Pressing the red Participate button leads you to a page where you have to agree with those rules. You will not be able to submit any results before agreeing with the rules.
Note: Before trying to submit results, please read the Submission instructions section on this page.
VQGeneration Task (VQG)
VQG is introduced for the first time in this third edition of the VQA-Med challenge. The task consists in generating relevant natural language questions about radiology images using their visual content.
The datasets are available under the “Resources” tab.
Training and Validation Datasets:
- Training set: 780 radiology images with 2,156 associated questions.
Validation set: 141 radiology images with 164 questions.
We provided the answers as additional annotations if needed to train the VQG systems, we will NOT provide the answers in the test set.
Participants will be tasked with generating distinct questions that are relevant to the visual content of the test images (minimum 1 and maximum 7 questions for each test image).
- The VQG test set will include only images (without answers).
The VQA-Med-2019 and VQA-Med-2018 datasets could be used as additional training data:
- 25/02/2020: Release of the training and validation datasets
- 10/04/2020: Release of the test set
- 10/05/2020: Run submission deadline
As soon as the submission is open, you will find a “Create Submission” button on this page (next to the tabs).
Before being allowed to submit your results, you have to first press the red participate button, which leads you to a page where you have to accept the challenges rules.
More information regarding the submission instructions will be released soon.
More information regarding the evaluation criteria will be released soon.
Note: In order to participate in this challenge you have to sign an End User Agreement (EUA). You will find more information on the ‘Resources’ tab.
ImageCLEF lab is part of the Conference and Labs of the Evaluation Forum: CLEF 2020. CLEF 2020 consists of independent peer-reviewed workshops on a broad range of challenges in the fields of multilingual and multimodal information access evaluation, and a set of benchmarking activities carried in various labs designed to test different aspects of mono and cross-language Information retrieval systems. More details about the conference can be found here .
Submitting a working note with the full description of the methods used in each run is mandatory. Any run that could not be reproduced thanks to its description in the working notes might be removed from the official publication of the results. Working notes are published within CEUR-WS proceedings, resulting in an assignment of an individual DOI (URN) and an indexing by many bibliography systems including DBLP. According to the CEUR-WS policies, a light review of the working notes will be conducted by ImageCLEF organizing committee to ensure quality. As an illustration, ImageCLEF 2019 working notes (task overviews and participant working notes) can be found within CLEF 2019 CEUR-WS proceedings.
Participants of this challenge will automatically be registered at CLEF 2020. In order to be compliant with the CLEF registration requirements, please edit your profile by providing the following additional information:
Regarding the username, please choose a name that represents your team.
This information will not be publicly visible and will be exclusively used to contact you and to send the registration data to CLEF, which is the main organizer of all CLEF labs
Participating as an individual (non affiliated) researcher
We welcome individual researchers, i.e. not affiliated to any institution, to participate. We kindly ask you to provide us with a motivation letter containing the following information:
the presentation of your most relevant research activities related to the task/tasks
your motivation for participating in the task/tasks and how you want to exploit the results
a list of the most relevant 5 publications (if applicable)
the link to your personal webpage
The motivation letter should be directly concatenated to the End User Agreement document or sent as a PDF file to bionescu at imag dot pub dot ro. The request will be analyzed by the ImageCLEF organizing committee. We reserve the right to refuse any applicants whose experience in the field is too narrow, and would therefore most likely prevent them from being able to finish the task/tasks.
Information will be posted after the challenge ends.
ImageCLEF 2020 is an evaluation campaign that is being organized as part of the CLEF initiative labs. The campaign offers several research tasks that welcome participation from teams around the world. The results of the campaign appear in the working notes proceedings, published by CEUR Workshop Proceedings (CEUR-WS.org). Selected contributions among the participants, will be invited for publication in the following year in the Springer Lecture Notes in Computer Science (LNCS) together with the annual lab overviews.
- You can ask questions related to this challenge on the Discussion Forum. Before asking a new question please make sure that question has not been asked before.
- Click on Discussion tab above or direct link: https://discourse.aicrowd.com/c/imageclef-2020-vqa-med-vqg
We strongly encourage you to use the public channels mentioned above for communications between the participants and the organizers. In extreme cases, if there are any queries or comments that you would like to make using a private communication channel, then you can send us an email at :
You can find additional information on the challenge here: https://www.imageclef.org/2020/medical/vqa
Mailing list: https://groups.google.com/d/forum/imageclef-vqa-med