This contribution proposes a compositionality architecture for visual object categorization, i.e., learning and recognizing multiple visual object classes in unsegmented, cluttered...
We consider the problem of visual categorization with minimal supervision during training. We propose a partbased model that loosely captures structural information. We represent ...
Skeletonization algorithms typically decompose an object’s
silhouette into a set of symmetric parts, offering a
powerful representation for shape categorization. However,
havi...
Alex Levinshtein, Sven Dickinson, Cristian Sminchi...
Bag-of-features (BoF) deriving from local keypoints has recently appeared promising for object and scene classification. Whether BoF can naturally survive the challenges such as ...
We propose a novel and robust model to represent and learn generic 3D object categories. We aim to solve the problem of true 3D object categorization for handling arbitrary rotati...