Call For Participation: ImageCLEF 2026: Multimodal Challenges in Medicine, Science, Agritech, and Security
18 views
Skip to first unread message
Cristian Stanciu
Feb 4, 2026, 9:40:18 AM (yesterday) Feb 4
to Machine Learning News
[Apologies for multiple postings]
ImageCLEF 2026: Multimodal Challenges in Medicine, Science, Agritech, and Security
***CALL FOR PARTICIPATION***
ImageCLEF 2026 is an evaluation campaign that is being organized as part of the CLEF (Conference and Labs of the Evaluation Forum) 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) and are presented in the CLEF conference. 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.
Target communities involve (but are not limited to): information retrieval (text, vision, audio, multimedia, social media, sensor data, etc.), machine learning, deep learning, data mining, natural language processing, image and video processing, computer vision, with special attention to the challenges of multi-modality, multi-linguality, and data generation.
***2026 Tasks***
ImageCLEFmedical Caption: Concept Detection, Caption Prediction and Explainability in Radiology images
ImageCLEFmedical Visual Question Answering for Gastrointestinal (GI) Imaging
ImageCLEFmedical GANs: Evaluation of Quality and Privacy in Synthetic Medical Images Created via GANs
ImageCLEFmedical MEDIQA-CORE: Multimodal Reasoning & Reconciliation in Radiology,
ImageCLEF ToPicto: Text-to-Pictogram Translation and Pictogram Prediction
ImageCLEF Multimodal Reasoning: Multi-domain, Multi-language Viaual Question Answering
ImageCLEF Ai4Agriculture: AI in Agriculture, Agriculture Potential Estimation, Crop Identification
ImageCLEF Deepfake: Few-Shot Deepfake Generation and Deepfake Detection in Images and Audio
#ImageCLEFmedical Caption (10th edition)
Interpreting and summarizing the insights gained from medical images such as radiology output is a time-consuming task that involves highly trained experts and often represents a bottleneck in clinical diagnosis pipelines. The Automatic Image Captioning task is split into 2 subtasks: Concept Detection Task, based on identifying the presence and location of relevant concepts in a large corpus of medical images and the Caption Prediction Task, where participating systems are tasked with composing coherent captions for the entirety of an image.
#ImageCLEFmedical Visual Question Answering (4th edition)
The 4th MEDVQA-GI challenge advances Visual Question Answering (VQA) for gastrointestinal (GI) imaging with a continued emphasis on explainability, clinical safety, and multimodal reasoning. The first subtask focuses on developing models to accurately answer clinically relevant questions from GI endoscopy images, while the second subtask focuses on explainability through multimodal justifications, that combine textual and visual evidence aligned with medical reasoning.
#ImageCLEFmedical GANs (4th edition)
ImageCLEFmedical-GANs 2026 evaluates the quality and privacy of synthetic tuberculosis CT images, with a new generation task requiring participants to produce images while analyzing risks of patient re-identification and data leakage.
#ImageCLEFmedical MEDIQA-CORE (1st edition)
The new MEDIQA-CORE 2026 task focuses on multimodal reasoning in radiology, evaluating models on tumor diagnosis using images and reports and on detecting and reconciling discrepancies between conflicting radiology interpretations.
#ImageCLEF ToPicto (3rd edition)
ImageCLEFtoPicto 2026 aims to advance research on automatically converting written English text into meaningful sequences of pictograms to support alternative and augmentative communication. The challenge introduces an English text-to-pictogram translation task using aligned text and pictogram data, as well as a new task focused on predicting the most likely next pictogram in an ongoing sequence.
#ImageCLEF Multimodal Reasoning (2nd edition)
The second edition of the Multimodal Reasoning task evaluates the reasoning abilities of vision–language models through multilingual visual question answering, expanding the multiple-choice setting and introducing open-ended questions that require generating answers directly from visual and textual content.
#ImageCLEF Ai4Agriculture (1st edition)
The AI for agriculture task includes two sub-tasks: AgriPotential, which evaluates models’ ability to estimate land suitability for different crop types using multi-temporal and multi-spectral Sentinel-2 imagery from southern France, and DACIA5, which focuses on crop identification and early crop recognition using Sentinel-1 and Sentinel-2 data over agricultural parcels in Romania.
#ImageCLEF Deepfake (1st edition)
The first edition of the Deepfake task evaluates both generation and detection of visual and audio deepfakes, measuring how convincingly deepfakes can be created and how effectively state-of-the-art methods can detect them across multiple evaluation criteria.
*** IMPORTANT DATES ***
(may vary depending on the task)
- Run submission deadline: May 7, 2026
- Working notes submission: May 28, 2026
- CLEF 2026 conference: September 21-24, 2026, Jena, Germany
*** REGISTRATION ***
For registration, follow the instructions here: https://www.imageclef.org/2026, in the "Participant registration" section.
*** OVERALL COORDINATION ***
Bogdan Ionescu, Politehnica University of Bucharest, Romania
Henning Müller, HES-SO, Sierre, Switzerland
Cristian Stanciu, Politehnica University of Bucharest, Romania
On behalf of the organizers,
Cristian Stanciu
Reply all
Reply to author
Forward
0 new messages