We gave a tutorial on “Image Tag Assignment, Refinement and Retrieval” at CVPR 2016, based on our survey. The focus is on challenges and solutions for content-based image retrieval in the context of online image sharing. We present a unified review on three problems: tag assignment, refinement, and tag-based image retrieval.
The slides are available on this page.
Everything you wanted to know about image tagging, tag refinement and social image retrieval. Our paper has been (finally) accepted to ACM Computing Surveys! This is a titanic effort, by Xirong Li, Tiberio Uricchio, myself, Marco Bertini, Cees Snoek and Alberto Del Bimbo, to structure the growing literature in the field, understand the ingredients of the main works, clarify their connections and difference, and recognize their merits and limitations.
A pre-print is available on arXiv and the source code is on GitHub.
MICC laboratories, Florence, 31th October 2013 (10.15-13.15). Course on Multimedia Databases (DBMM) – laboratory lecture.
- Goal: logo recognition in web images.
- Dataset/testset: find 4 different logos vs 110 images.
- Evaluation metrics: recognition performances will be evaluated in terms of mean Average Precision (mAP).
Instructors: Lamberto Ballan, Lorenzo Seidenari.
Download Software & Dataset 
(* based on VLFeat library by A. Vedaldi)
Final results (ranking): http://goo.gl/o5DCG5
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We gave a tutorial on “Image Tag Assignment, Refinement and Retrieval” at CVPR 2016, based on our survey. The focus is on challenges and solutions for content-based image retrieval in the context of online image sharing. We present a unified review on three problems: tag assignment, refinement, and tag-based image retrieval.
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