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...
This paper presents a method for face recognition across large changes in viewpoint. Our method is based on a Morphable Model of 3D faces that represents face-specific information...
Volker Blanz, Patrick Grother, P. Jonathon Phillip...
Abstract. Natural scenes consist of a wide variety of stochastic patterns. While many patterns are represented well by statistical models in two dimensional regions as most image s...
Abstract. Optical music recognition (OMR) enables librarians to digitise early music sources on a large scale. The cost of expert human labour to correct automatic recognition erro...
Laurent Pugin, John Ashley Burgoyne, Ichiro Fujina...
This paper presents a multi-scale generative model for representing animate shapes and extracting meaningful parts of objects. The model assumes that animate shapes (2D simple clo...