Recognition of three dimensional (3D) objects in noisy and cluttered scenes is a challenging problem in 3D computer vision. One approach that has been successful in past research i...
Andrea Frome, Daniel Huber, Ravi Kolluri, Thomas B...
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
The context-centered approach to object detection and recognition is based on the intuition that the contextual information of real-world scenes provides relevant information for ...
Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurre...
Anna Bosch, Arnau Oliver, Robert Marti, Xavier Mu&...
We propose an hybrid and probabilistic classification of image regions belonging to scenes primarily containing natural objects, e.g. sky, trees, etc. as a first step in solving ...