2 citations · 5 across the 4 of their papers we have counts for
5 papers
Joint calibration of Ensemble of Exemplar SVMs
Davide Modolo, Alexander Vezhnevets, Olga Russakovsky +1
We present a method for calibrating the Ensemble of Exemplar SVMs model. Unlike the standard approach, which calibrates each SVM independently, our method optimizes their joint per…
Context Forest for efficient object detection with large mixture models
Davide Modolo, Alexander Vezhnevets, Vittorio Ferrari
We present Context Forest (ConF), a technique for predicting properties of the objects in an image based on its global appearance. Compared to standard nearest-neighbour techniques…
Object localization in ImageNet by looking out of the window
Alexander Vezhnevets, Vittorio Ferrari
We propose a method for annotating the location of objects in ImageNet. Traditionally, this is cast as an image window classification problem, where each window is considered indep…
An active search strategy for efficient object class detection
Abel Gonzalez-Garcia, Alexander Vezhnevets, Vittorio Ferrari
Object class detectors typically apply a window classifier to all the windows in a large set, either in a sliding window manner or using object proposals. In this paper, we develop…
Associative embeddings for large-scale knowledge transfer with self-assessment
Alexander Vezhnevets, Vittorio Ferrari
We propose a method for knowledge transfer between semantically related classes in ImageNet. By transferring knowledge from the images that have bounding-box annotations to the oth…