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CVPR
2010
IEEE
1135views Computer Vision» more  CVPR 2010»
16 years 2 months ago
Towards Weakly Supervised Semantic Segmentation by Means of Multiple Instance and Multitask Learning.
We address the task of learning a semantic segmentation from weakly supervised data. Our aim is to devise a system that predicts an object label for each pixel by making use of on...
Alexander Vezhnevets, Joachim Buhmann
ICRA
2009
IEEE
132views Robotics» more  ICRA 2009»
16 years 1 months ago
Smoothed Sarsa: Reinforcement learning for robot delivery tasks
— Our goal in this work is to make high level decisions for mobile robots. In particular, given a queue of prioritized object delivery tasks, we wish to find a sequence of actio...
Deepak Ramachandran, Rakesh Gupta
257
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ECCV
2010
Springer
15 years 11 months ago
Discriminative Tracking by Metric Learning
We present a discriminative model that casts appearance modeling and visual matching into a single objective for visual tracking. Most previous discriminative models for visual tra...
ECCV
2006
Springer
15 years 10 months ago
Learning Semantic Scene Models by Trajectory Analysis
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
Xiaogang Wang, Kinh Tieu, Eric Grimson
GRAPHICSINTERFACE
2000
15 years 8 months ago
Using a 3D Puzzle as a Metaphor for Learning Spatial Relations
We introduce a new metaphor for learning spatial relations--the 3D puzzle. With this metaphor users learn spatial relations by assembling a geometric model themselves. For this pu...
Bernhard Preim, Felix Ritter, Oliver Deussen, Thom...