We formulate a model for multi-class object detection in a multi-camera environment. From our knowledge, this is the first time that this problem is addressed taken into account ...
Xavier Boix, Gemma Roig, Horesh Ben Shitrit, Pasca...
Abstract. We consider the problem of detecting a large number of different classes of objects in cluttered scenes. We present a learning procedure, based on boosted decision stumps...
Antonio B. Torralba, Kevin P. Murphy, William T. F...
With recent advances in sensory and mobile computing technology, enormous amounts of data about moving objects are being collected. One important application with such data is aut...
Xiaolei Li, Jiawei Han, Sangkyum Kim, Hector Gonza...
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...