AuthorsB. Ionescu, H. Müller, R. Péteri, D. Dang-Nguyen, L. Zhou, L. Piras, M. Riegler, P. Halvorsen, M. Tran, M. Lux et al.
EditorsJ. M. Jose, E. Yilmaz, J. Magalhães, P. Castells, N. Ferro, M. J. Silva and F. Martins
TitleImageCLEF 2020: Multimedia Retrieval in Lifelogging, Medical, Nature, and Internet Applications
AfilliationMachine Learning
Project(s)Department of Holistic Systems
StatusPublished
Publication TypeProceedings, refereed
Year of Publication2020
Conference NameEuropean Conference on Information Retrieval
Pagination533 - 541
PublisherSpringer International Publishing
Place PublishedCham
ISBN Number978-3-030-45441-8
ISSN Number0302-9743
Abstract

This paper presents an overview of the 2020 ImageCLEF lab that will be organized as part of the Conference and Labs of the Evaluation Forum—CLEF Labs 2020 in Thessaloniki, Greece. ImageCLEF is an ongoing evaluation initiative (run since 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2020, the 18th edition of ImageCLEF will organize four main tasks: (i) a Lifelog task (videos, images and other sources) about daily activity understanding, retrieval and summarization, (ii) a Medical task that groups three previous tasks (caption analysis, tuberculosis prediction, and medical visual question answering) with new data and adapted tasks, (iii) a Coral task about segmenting and labeling collections of coral images for 3D modeling, and a new (iv) Web user interface task addressing the problems of detecting and recognizing hand drawn website UIs (User Interfaces) for generating automatic code. The strong participation, with over 235 research groups registering and 63 submitting over 359 runs for the tasks in 2019 shows an important interest in this benchmarking campaign. We expect the new tasks to attract at least as many researchers for 2020.

URLhttps://link.springer.com/chapter/10.1007/978-3-030-45442-5_69
DOI10.1007/978-3-030-45442-5_69
Citation Key27473

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