The k-NN graph has played a central role in increasingly popular data-driven techniques for
various learning and vision tasks; yet, finding an efficient and effective way to construct k-NN …

We propose a sketch‐based 3D shape retrieval system that is substantially more
discriminative and robust than existing systems, especially for complex models. The power …

Most of graph construction techniques assume a transductive setting in which the whole
data collection is available at construction time. Addressing graph construction for inductive …

In this paper, we propose a dynamic graph construction technique that inserts new samples
into a previously constructed graph, which reduces the computational time and complexity of …

The relative neighborhood graph of a collection of objects assigns an edge to a pair of
objects (A, B), provided that no other object is closer to both A and B, than A and B are to …

This paper addresses the problem of the incremental construction of an indexing structure,
namely a proximity graph, for large image collections. To this purpose, a local update …

We present in this paper a tool called EXOD (EXploration of Open Datasets) for the visual
analysis of a large collection of open datasets. EXOD aims at helping the users to find …

Most of graph construction techniques assume a transductive setting in which the whole
data collection is available at construction time. Addressing graph construction for inductive …

Similarity search for information retrieval on a variety of datasets relies on a notion of
neighborhood, frequently using binary relationships such as the k NN approach. We …

Indexing is the most effective technique to speed up queries in databases. While traditional
indexing approaches are used for exact search, a query object may not be always identical …