This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
In this paper, we present a real-time algorithm for 3D object detection in images. Our method relies on the Ullman and Basri [13] theory which claims that the same object under di...
Recognition of object categories from their images is extremely challenging due to the large intra-class variations, and variations in pose, illumination and scale, in addition to...
We present a novel Object Recognition approach based on affine invariant regions. It actively counters the problems related to the limited repeatability of the region detectors, an...
Vittorio Ferrari, Tinne Tuytelaars, Luc J. Van Goo...
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...