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» Learning Hierarchical Models of Scenes, Objects, and Parts
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ECCV
2008
Springer
15 years 11 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
WAPCV
2007
Springer
15 years 3 months ago
Context Driven Focus of Attention for Object Detection
Abstract. Context plays an important role in general scene perception. In particular, it can provide cues about an object’s location within an image. In computer vision, object d...
Roland Perko, Ales Leonardis
CVIU
2006
162views more  CVIU 2006»
14 years 9 months ago
Unsupervised scene analysis: A hidden Markov model approach
This paper presents a new approach to scene analysis, which aims at extracting structured information from a video sequence using directly low-level data. The method models the se...
Manuele Bicego, Marco Cristani, Vittorio Murino
3DPVT
2002
IEEE
209views Visualization» more  3DPVT 2002»
15 years 2 months ago
Improving Environment Modelling by Edge Occlusion Surface Completion
Reconstruction of 3D models from range images usually focuses on complex objects completely contained in the field of view. Using range images to reconstruct a whole environment ...
Umberto Castellani, Salvatore Livatino, Robert B. ...
ICASSP
2011
IEEE
14 years 1 months ago
A visual attention model combining top-down and bottom-up mechanisms for salient object detection
Selective attention in the human visual system is performed as the way that humans focus on the most important parts when observing a visual scene. Many bottom-up computational mo...
Yuming Fang, Weisi Lin, Chiew Tong Lau, Bu-Sung Le...