Many diagrams contain compound objects composed of parts. We propose a recognition framework that learns parts in an unsupervised way, and requires training labels only for compou...
We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden conditi...
Abstract. Clustering data described by categorical attributes is a challenging task in data mining applications. Unlike numerical attributes, it is difficult to define a distance b...
Learning Object repositories play a key role in the vision of reusable learning contents and learning designs, serving as providers for learning-oriented artefacts. Nevertheless, ...
Detecting objects in cluttered scenes and estimating articulated human body parts are two challenging problems in computer vision. The difficulty is particularly pronounced in ac...