Generative regularization with latent topics for discriminative object recognition
We group parts and instances to model topics of objects for the recognition problem. We jointly learn to classify objects as well as to perform the grouping of parts and instances into topics. The grouping improves performance in PASCAL VOC dataset and the MIT indoor dataset.
visual object recognition part-based models non-negative matrix factorization latent svm mixture models