This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of e...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
Local photometric descriptors are a crucial low level component of numerous computer vision algorithms. In practice, these descriptors are constructed to be invariant to a class o...
Edgar Lobaton, Ramanarayan Vasudevan, Ron Alterovi...
We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...
—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...
— When using appearance-based recognition for self-localization of mobile robots, the images obtained during the exploration of the environment need to be efficiently stored in t...