Internship/PhD scholarship at INRIA - LEAR research group INRIA Grenoble
The goal of this internship/PhD is to improve the current performance
of object detection systems on several fronts. The ideal candidate
will first do an internship and then continue with a PhD.
Applying directly for a PhD is also possible. Please do not apply for
In order to improve current object detectors, the objectives here are
two-fold: (a) to make the representation more robust and distinctive
and (b) to collect additional training data to better model the
variability of object categories.
To improve the representation, which is currently either based on HOG
descriptors, or local features like SIFT encoded by bag-of-word
histograms or Fisher vectors, we will design mid-level or
high-level features, for example based on image segmentation and
To collect additional training data, object detectors will be trained
in a weakly supervised scenario, which will result in significantly
more data for training. Initially, we will train object detectors
from images for which no ground-truth object locations are known, but
only a image-wide label that indicates the presence of one or more
instances of the category in the image. We will, then, move to mixed
scenarios where a few annotations are available.
* Master degree (preferably in Computer Science or Applied Mathematics; Electrical Engineering will also be considered)
* Solid programming skills; the project involves programming in C
* Solid mathematics knowledge (especially linear algebra and statistics)
* Creative and highly motivated
* Fluent in English, both written and spoken
* Prior knowledge in the areas of computer vision, machine learning or data mining is a plus
Duration: 3-4 years
Start date: As soon as possible. No later than October 2014.
Location: INRIA Grenoble, France. Grenoble lies in the French Alpes
and offers ideal conditions for skiing, hiking, climbing etc.
Contact: Jakob Verbeek (Jakob.Verbeek(at)inria.fr) and Cordelia Schmid
Please send applications via email, including:
* a complete CV
* graduation marks
* two reference letters