Convolutional neural network architecture for geometric matching
Texte intégral
Documents relatifs
The a contrario algorithm is compared with the method mentioned in section 1 (step 2), i.e., NN-T matching (nearest neighbor matching based on the Euclidean distance, and threshold
Some convolutional filters from the first layer of the regressor, acting on the tentative correspondence map, show preferences to spatially co-located features that
To make the model tractable we also introduced a matching graph clustered using connected component clustering, that can be used to quickly organize very large image collections,
The literature on learning similarity/dissimilarity matching functions can be roughly categorized into two parts according to whether the objective is to minimize an error rate on
Table 3: The probabilistic matching rules among the related pairs ID Category Probabilistic matching rules R 1 class two classes probably match if their fathers match R 2 class
We compare our algorithms (CSv1), which uses the first set of edit opera- tions, and (CSv2), which uses the second set of edit operations, with three other approaches: a graph
In this work, we propose to augment image evidence with soft geometric constraints to learn object instance matching in street-level images at large scale end-to-end.. Our ultimate
Unité de recherche INRIA Rennes, Irisa, Campus universitaire de Beaulieu, 35042 RENNES Cedex Unité de recherche INRIA Rhône-Alpes, 46 avenue Félix Viallet, 38031 GRENOBLE Cedex 1.