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ICCV
2011
IEEE
12 years 8 months ago
Actively Selecting Annotations Among Objects and Attributes
We present an active learning approach to choose image annotation requests among both object category labels and the objects’ attribute labels. The goal is to solicit those labe...
Adriana Kovashka, Sudheendra Vijayanarasimhan, Kri...
ICDAR
2005
IEEE
14 years 1 months ago
Learning Diagram Parts with Hidden Random Fields
Many diagrams contain compound objects composed of parts. We propose a recognition framework that learns parts in an unsupervised way, and requires training labels only for compou...
Martin Szummer
3DIM
2011
IEEE
12 years 8 months ago
A Non-cooperative Game for 3D Object Recognition in Cluttered Scenes
Abstract—During the last few years a wide range of algorithms and devices have been made available to easily acquire range images. To this extent, the increasing abundance of dep...
Andrea Albarelli, Emanuele Rodolà, Filippo ...
ICANN
2005
Springer
14 years 1 months ago
Online Learning for Object Recognition with a Hierarchical Visual Cortex Model
We present an architecture for the online learning of object representations based on a visual cortex hierarchy developed earlier. We use the output of a topographical feature hier...
Stephan Kirstein, Heiko Wersing, Edgar Körner
IJCV
2008
266views more  IJCV 2008»
13 years 8 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...