In this paper, we propose a new technique to perform figure-ground segmentation in image sequences of moving objects under varying illumination conditions. Unlike most of the alg...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
We present an approach for online learning of discriminative appearance models for robust multi-target tracking in a crowded scene from a single camera. Although much progress has...
Local intrinsic dimension estimation has been shown to be useful for many tasks such as image segmentation, anomaly detection, and de-biasing global dimension estimates. Of partic...
We present a new method for efficiently simulating the scattering of light within participating media. Using a theoretical reformulation of volumetric photon mapping, we develop a...
Wojciech Jarosz, Matthias Zwicker, Henrik Wann Jen...
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...