The main focus of our workshop is on computer vision tasks that operate at instance-level, including both recognition (instance-level recognition - ILR) and generation (instance-level generation - ILG), denoted as ILR+G. More precisely, ILR+G is the task of identifying, comparing, and generating images of specific objects, scenes, or events.

This year, we will organize a call for papers, and host keynote talks by renowned speakers and invited paper talks from the main conference.

The 2026 Instance-Level Recognition and Generation (ILR+G) Workshop is a follow-up of seven successful editions of our previous workshops — the first two having focused only on landmark recognition (CVPRW18, CVPRW19), the following ones expanding to the domains of artworks and products (ECCVW20, ICCVW21), introducing the universal image embedding problem (ECCVW22, ECCVW24), and the latest one expanding the scope of our workshop to ILG and the potential synergy between ILG and ILR (ICCVW25).

We call for novel and unpublished work in the format of long papers (14 pages excluding references) and short papers (4 pages excluding references). Papers should follow the ECCV proceedings style and will undergo double-blind peer review. Selected long papers will be invited for oral presentations; all accepted papers will be presented as posters. Only long papers will be published in the ECCV workshop proceedings. This year, financial awards will be given to the best papers, and student support grants will be provided to eligible participants. All submissions will be handled electronically via the OpenReview submission system.