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» Probabilistic Scene Models for Image Interpretation
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85
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SIGIR
2005
ACM
15 years 3 months ago
A database centric view of semantic image annotation and retrieval
We introduce a new model for semantic annotation and retrieval from image databases. The new model is based on a probabilistic formulation that poses annotation and retrieval as c...
Gustavo Carneiro, Nuno Vasconcelos
PCI
2005
Springer
15 years 3 months ago
Unsupervised Learning of Multiple Aspects of Moving Objects from Video
A popular framework for the interpretation of image sequences is based on the layered model; see e.g. Wang and Adelson [8], Irani et al. [2]. Jojic and Frey [3] provide a generativ...
Michalis K. Titsias, Christopher K. I. Williams
NIPS
2008
14 years 11 months ago
Supervised Dictionary Learning
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
CVPR
2006
IEEE
15 years 11 months ago
Putting Objects in Perspective
Image understanding requires not only individually estimating elements of the visual world but also capturing the interplay among them. In this paper, we provide a framework for p...
Derek Hoiem, Alexei A. Efros, Martial Hebert
98
Voted
ICASSP
2010
IEEE
14 years 10 months ago
Supervised topic model for automatic image annotation
This paper presents a new probabilistic model for the task of image annotation. Our model, which we call sLDA-bin, extends supervised Latent Dirichlet Allocation (sLDA) model to h...
Duangmanee Putthividhya, Hagai Thomas Attias, Srik...