We address the problem of fast, large scale sketch-based image retrieval, searching in a database of over one million images. We show that current retrieval methods do not scale w...
Mathias Eitz, Kristian Hildebrand, Tamy Boubekeur,...
In most IR clustering problems, we directly cluster the documents, working in the document space, using cosine similarity between documents as the similarity measure. In many real...
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
Besides search, complete inference methods can also be used to solve soft constraint problems. Their main drawback is the high spatial complexity. To improve its practical usage, w...
Conventional approaches to image retrieval are based on the assumption that relevant images are physically near the query image in some feature space. This is the basis of the clu...