SISAP 2024 Indexing Challenge

The International Conference on Similarity Search and Applications (SISAP) is an annual forum for researchers and application developers in the area of similarity data management. It aims at the technological problems shared by numerous application domains, such as data mining, information retrieval, multimedia, computer vision, pattern recognition, computational biology, geography, biometrics, machine learning, and many others that use similarity search as a necessary supporting service. Machine learning, dense retrieval, and multimedia indexing have taken the scene of similarity search as the most challenging task among applications. This call reflects on this observation.

The SISAP Indexing Challenge 2024 invites researchers and practitioners to participate in three exciting tasks aimed at advancing the state-of-the-art in similarity search and indexing. The challenge provides a platform to showcase innovative solutions and push the boundaries of efficiency and effectiveness in large-scale similarity search.

Important information


Important dates


We expect that participants prepare a detailed report of their solution in a typical SISAP's shortpaper format with a focus on reproducibility and comparing their speedup against a brute force solution in its machine and the resulting quality w.r.t. recall. Organizers and an ad-hoc committee will review these short papers if the number of papers is large, looking to increase the paper's quality. All participants can submit a report regardless of its final rank position. As in other SISAP's tracks and sessions, the acceptance will be based on the quality of contribution and the manuscript itself.

Past editions

In 2023 we launched the SISAP 2023 Indexing Challenge with a test bed to compare new and existing indexing algorithms in three common tasks.

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