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 (, ), the following ones expanding to the domains of artworks and products (, ), introducing the universal image embedding problem (, ), and the latest one expanding the scope of our workshop to ILG and the potential synergy between ILG and ILR ().
Google DeepMind
Google DeepMind
xAI
Czech Technical University
The University of Osaka
Google DeepMind
Czech Technical University (Primary Contact)
Czech Technical University
The University of Osaka
Amazon
Czech Technical University
Amazon
The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.
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