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» Generation of Semantic Regions from Image Sequences
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CVPR
2008
IEEE
14 years 10 months ago
Latent topic random fields: Learning using a taxonomy of labels
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Xuming He, Richard S. Zemel
SCIA
2007
Springer
14 years 2 months ago
Pseudo-real Image Sequence Generator for Optical Flow Computations
Abstract. The availability of ground-truth flow field is crucial for quantitative evaluation of any optical flow computation method. The fidelity of test data is also important...
Vladimír Ulman, Jan Hubený
MM
2009
ACM
217views Multimedia» more  MM 2009»
14 years 3 months ago
Label to region by bi-layer sparsity priors
In this work, we investigate how to automatically reassign the manually annotated labels at the image-level to those contextually derived semantic regions. First, we propose a bi-...
Xiaobai Liu, Bin Cheng, Shuicheng Yan, Jinhui Tang...
NIPS
2003
13 years 10 months ago
A Model for Learning the Semantics of Pictures
We propose an approach to learning the semantics of images which allows us to automatically annotate an image with keywords and to retrieve images based on text queries. We do thi...
Victor Lavrenko, R. Manmatha, Jiwoon Jeon
ICMCS
2006
IEEE
183views Multimedia» more  ICMCS 2006»
14 years 2 months ago
Region Enhanced Scale-Invariant Saliency Detection
Saliency measures the low-level stimuli to human vision, and serves as an alternative to semantic image understanding. This paper presents a region enhanced scale-invariant salien...
Feng Liu, Michael Gleicher