Current computational models of visual attention focus on bottom-up information and ignore scene context. However, studies in visual cognition show that humans use context to faci...
Aude Oliva, Antonio B. Torralba, Monica S. Castelh...
In this paper an efficient method of small object localization is proposed that integrates detection and tracking. The system is initialized using a strong detector and then it lo...
Abstract. In moving object databases, many authors assume that number and position of objects to be processed are always known in advance. Detecting an unknown moving object and pu...
We propose Recursive Compositional Models (RCMs) for simultaneous multi-view multi-object detection and parsing (e.g. view estimation and determining the positions of the object s...
Leo Zhu, Yuanhao Chen, Antonio Torralba, William F...
Abstract. We consider the problem of detecting a large number of different classes of objects in cluttered scenes. We present a learning procedure, based on boosted decision stumps...
Antonio B. Torralba, Kevin P. Murphy, William T. F...