• Dense segmentation-aware descriptors 

      Trulls Fortuny, Eduard; Kokkinos, Iasonas; Sanfeliu Cortés, Alberto; Moreno-Noguer, Francesc (2013)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      In this work we exploit segmentation to construct appearance descriptors that can robustly deal with occlusion and background changes. For this, we downplay measurements coming from areas that are unlikely to belong to the ...
    • Dense segmentation-aware descriptors 

      Trulls Fortuny, Eduard; Kokkinos, Iasonas; Sanfeliu Cortés, Alberto; Moreno-Noguer, Francesc (Springer, 2016)
      Capítol de llibre
      Accés restringit per política de l'editorial
      Dense descriptors are becoming increasingly popular in a host of tasks, such as dense image correspondence, bag-of-words image classification, and label transfer. However, the extraction of descriptors on generic image ...
    • Discriminative learning of deep convolutional feature point descriptors 

      Simó Serra, Edgar; Trulls Fortuny, Eduard; Ferraz, Luis; Kokkinos, Iasonas; Fua, Pascal; Moreno-Noguer, Francesc (Institute of Electrical and Electronics Engineers (IEEE), 2015)
      Text en actes de congrés
      Accés obert
      Deep learning has revolutionalized image-level tasks such as classification, but patch-level tasks, such as correspondence, still rely on hand-crafted features, e.g. SIFT. In this paper we use Convolutional Neural Networks ...
    • Segmentation-aware deformable part models 

      Tsogkas, Stavros; Kokkinos, Iasonas; Trulls Fortuny, Eduard; Sanfeliu Cortés, Alberto; Moreno-Noguer, Francesc (Institute of Electrical and Electronics Engineers (IEEE), 2014)
      Text en actes de congrés
      Accés obert
      In this work we propose a technique to combine bottom- up segmentation, coming in the form of SLIC superpixels, with sliding window detectors, such as Deformable Part Models (DPMs). The merit of our approach lies in ...