Handling large amounts of data, such as large image databases, requires the use of approximate nearest neighbor search techniques. Recently, Hamming embedding methods such as spec...
We present a novel weighted approach for shrinkage functions learning in image denoising. The proposed approach optimizes the shape of the shrinkage functions and maximizes denois...
Sampling inequalities give a precise formulation of the fact that a differentiable function cannot attain large values, if its derivatives are bounded and if it is small on a suff...
We present an efficient compression scheme for animated sequences of triangular meshes of the same connectivity. The proposed algorithm exploits the temporal coherence of the geo...
This paper describes a deterministic approach for the typification of buildings which uses several levels of details for the derivation of intermediate scales. The typification pro...