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Titlebook: Dense Image Correspondences for Computer Vision; Tal Hassner,Ce Liu Book 2016 Springer International Publishing Switzerland 2016 Annotatio

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SIFTpack: A Compact Representation for Efficient SIFT Matchings large, as is often the case, computing these distances can be extremely time consuming. We propose the SIFTpack: a compact way of storing SIFT descriptors, which enables significantly faster calculations between sets of SIFTs than the current solutions. SIFTpack can be used to represent SIFTs dens
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Depth Transfer: Depth Extraction from Videos Using Nonparametric Samplingrate this method in cases where existing methods fail (nontranslating cameras and dynamic scenes). This technique is applicable to single images as well as videos. For videos, local motion cues are used to improve the inferred depth maps, while optical flow is used to ensure temporal depth consisten
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Nonparametric Scene Parsing via Label Transferels for images, scenes, and objects. In this chapter, we propose a novel, nonparametric approach for object recognition and scene parsing using a new technology we name .. For an input image, our system first retrieves its nearest neighbors from a large database containing fully annotated images. Th
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Joint Inference in Weakly-Annotated Image Datasets via Dense Correspondenceision rely on a large corpus of densely labeled images. However, for large, modern image datasets, such labels are expensive to obtain and are often unavailable. We establish a large-scale graphical model spanning all labeled and unlabeled images, then solve it to infer pixel labels . for all images
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DOMAINS – A Dynamics Ontology: Perdurantsxplore the scale changes. Our approach achieves a similar performance as the SIFT flow method for natural scenes but obtains significant improvement for the images with large scale differences. Compared with a recent method that addresses a similar problem, our approach shows its advantage being more effective and efficient.
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DOMAINS – An Ontology: Internal Qualitiesn time, for both finding nearest neighbors and computing all distances between all descriptors. The usefulness of SIFTpack is demonstrated as an alternative implementation for .-means dictionaries of visual words and for image retrieval.
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