Pedestrian detection is an important problem in computer vision due to its importance for applications such as visual surveillance, robotics, and automotive safety. This paper push...
Recovering the 3D shape of deformable surfaces from single images is difficult because many different shapes have very similar projections. This is commonly addressed by restricti...
Image classification is a critical task for both humans and computers. One of the challenges lies in the large scale of the semantic space. In particular, humans can recognize tens...
Abstract. We describe a single-shot method to differentiate unscattered and scattered components of light transmission through a heterogeneous translucent material. Directly-transm...
Abstract. Much recent research in human activity recognition has focused on the problem of recognizing simple repetitive (walking, running, waving) and punctual actions (sitting up...
Grouping and Abstraction Using Simple Part Models Pablo Sala and Sven Dickinson Department of Computer Science, University of Toronto, Toronto ON, Canada We address the problem of ...
Abstract. Detecting contour closure, i.e., finding a cycle of disconnected contour fragments that separates an object from its background, is an important problem in perceptual gro...
We introduce a new descriptor for images which allows the construction of efficient and compact classifiers with good accuracy on object category recognition. The descriptor is the...
Abstract. Even a relatively unstructured captioned image set depicting a variety of objects in cluttered scenes contains strong correlations between caption words and repeated visu...
This paper presents a method for learning artistic portrait lighting template from a dataset of artistic and daily portrait photographs. The learned template can be used for (1) cl...