no code implementations • 5 Jul 2022 • Suraj Kothawade, Donna Roy, Michele Fenzi, Elmar Haussmann, Jose M. Alvarez, Christoph Angerer
Existing semantic image retrieval methods often focus on mining for larger sized geographical landmarks, and/or require extra labeled data, such as images/image-pairs with similar objects, for mining images with generic objects.
no code implementations • 9 Apr 2020 • Elmar Haussmann, Michele Fenzi, Kashyap Chitta, Jan Ivanecky, Hanson Xu, Donna Roy, Akshita Mittel, Nicolas Koumchatzky, Clement Farabet, Jose M. Alvarez
We have built a scalable production system for active learning in the domain of autonomous driving.
no code implementations • ICCV 2015 • Michele Fenzi, Laura Leal-Taixe, Jorn Ostermann, Tinne Tuytelaars
In this paper, we treat the problem of continuous pose estimation for object categories as a regression problem on the basis of only 2D training information.
no code implementations • CVPR 2014 • Laura Leal-Taixe, Michele Fenzi, Alina Kuznetsova, Bodo Rosenhahn, Silvio Savarese
We present a novel method for multiple people tracking that leverages a generalized model for capturing interactions among individuals.
no code implementations • CVPR 2013 • Michele Fenzi, Laura Leal-Taixe, Bodo Rosenhahn, Jorn Ostermann
In this paper, we propose a method for learning a class representation that can return a continuous value for the pose of an unknown class instance using only 2D data and weak 3D labelling information.