collaborators

10 papers

cs.CV2025

SuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches

Rémi Giraud, Vinh-Thong Ta, Aurélie Bugeau +2

Superpixels have become very popular in many computer vision applications. Nevertheless, they remain underexploited since the superpixel decomposition may produce irregular and non…

cs.CV2025

Multi-Scale Superpatch Matching using Dual Superpixel Descriptors

Rémi Giraud, Merlin Boyer, Michaël Clément

Over-segmentation into superpixels is a very effective dimensionality reduction strategy, enabling fast dense image processing. The main issue of this approach is the inherent irre…

cs.CV2025

Texture Superpixel Clustering from Patch-based Nearest Neighbor Matching

Rémi Giraud, Yannick Berthoumieu

Superpixels are widely used in computer vision applications. Nevertheless, decomposition methods may still fail to efficiently cluster image pixels according to their local texture…

cs.CV2025

Robust superpixels using color and contour features along linear path

Rémi Giraud, Vinh-Thong Ta, Nicolas Papadakis

Superpixel decomposition methods are widely used in computer vision and image processing applications. By grouping homogeneous pixels, the accuracy can be increased and the decreas…

cs.CV2025

An Optimized PatchMatch for Multi-scale and Multi-feature Label Fusion

Rémi Giraud, Vinh-Thong Ta, Nicolas Papadakis +4

Automatic segmentation methods are important tools for quantitative analysis of Magnetic Resonance Images (MRI). Recently, patch-based label fusion approaches have demonstrated sta…

cs.CV2025

Evaluation Framework of Superpixel Methods with a Global Regularity Measure

Rémi Giraud, Vinh-Thong Ta, Nicolas Papadakis

In the superpixel literature, the comparison of state-of-the-art methods can be biased by the non-robustness of some metrics to decomposition aspects, such as the superpixel scale.…