Eventa

Challenge Overview Event-Enriched Image Captioning Event-Based Image Retrieval Challenge Rules Dataset Paper Submission Important Dates

The EVENTA 2025 Grand Challenge focuses on image-caption retrieval and generation. We aim to integrate contextual details and event-related information to create comprehensive, narrative-driven captions that go beyond simple visual analysis. Therefore, the captions provide richer, more comprehensive information about an image. These captions go beyond simple visual descriptions by offering deeper insights, including the names and attributes of objects, the timing, context, outcomes of events, and other crucial details - information that cannot be gleaned from merely observing the image.

🚀 Top-ranked teams will be invited to submit a paper to ACM Multimedia and present at the conference, subject to peer review.

To participate in the EVENTA 2025 Grand Challenge, please first register by submitting the form.

Track 1: Event-Enriched Image Captioning

This track aims to generate captions that provide richer, more comprehensive information about an image. These captions go beyond simple visual descriptions by offering deeper insights, including the names and attributes of objects, the timing, context, outcomes of events, and other crucial details—information that cannot be gleaned from merely observing the image. Given an image, participants are required to search relevant articles in a provided external database and extract necessary information to enrich the image caption. This retrieval augmentation generation track facilitates the creation of more coherent and detailed narratives, capturing not only the visible elements but also the underlying context and significance of the scene, ultimately offering a more complete understanding of what the image represents. More details here.

Track 2: Event-Based Image Retrieval

Given a realistic caption, participants are required to retrieve corresponding images from a provided database. This retrieval task is a fundamental task in computer vision and natural language processing that requires learning a joint representation space where visual and textual modalities can be meaningfully compared. Image retrieval with textual queries is widely used in search engines, medical imaging, e-commerce, and digital asset management. However, challenges remain, such as handling abstract or ambiguous queries, improving retrieval efficiency for large-scale datasets, and ensuring robustness to linguistic variations and biases in training data. This image retrieval track aims to tackle issues of realistic information from events in real life. More details here.

Challenge Rules

Participants are not allowed to annotate the test sets.
External datasets are permitted. However, participants may only use publicly accessible datasets and pre-trained models. The use of private datasets or pre-trained models is strictly prohibited.
Open sources are allowed. However, commercial tools, libraries, APIs, etc. are strictly prohibited.
Final scores are calculated based on performance on the Private Test set.
Participants must make their source code publicly available on GitHub to ensure reproducibility.
Participants must submit a detailed paper through the official challenge platform before the deadline to validate their solutions.
Late submissions will not be accepted.
Only registered teams that submit papers are eligible to win, but all participants’ scores will be recognized.

Dataset

EVENTA 2025 Grand Challenge uses OpenEvents V1 dataset.

Paper Submission

We accept papers which are up to 8 pages in ACM MM format, excluding references. Overlength papers will be rejected without review. Paper submissions must conform with the “double-blind” review policy. Submission policies adhere to the ACM MM 2025 submission policies.

We recommend participants to cite the Challenge Overview paper written by the organizers. This paper contains all the necessary information on the challenge definition and the dataset. Therefore, participants do not need to repeat to describe the challenge or the dataset in details. Instead, participants can exclusively present the motivation for their approach, explaining their method, showing and analyzing their results, and giving an outlook on future work, etc.

Submit your paper here.

Important Dates