This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Current object recognition systems can only recognize a limited number of object categories; scaling up to many categories is the next challenge. We seek to build a system to reco...
Bryan C. Russell, Antonio Torralba, Ce Liu, Robert...
We consider the task of estimating, from observed data, a probabilistic model that is parameterized by a finite number of parameters. In particular, we are considering the situat...
— This paper describes a robotic system that learns visual models of symmetric objects autonomously. Our robot learns by physically interacting with an object using its end effec...
Detecting and segmenting free-form objects from cluttered backgrounds is a challenging problem in computer vision. Signature detection in document images is one classic example an...
Guangyu Zhu, Yefeng Zheng, David S. Doermann, Stef...