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Training with Corrupted Labels to Reinforce a Probably Correct Teamsport Player Detector
TLDR
A classifier is trained to differentiate false and true positives among the detections computed based on a foreground mask analysis in a sport analysis context where people deformations are important, which makes it important to adapt the classifier to the case at hand, so as to take the teamsport color and the background appearance into account. Expand
A robust nonlinear scale space change detection approach for SAR images
In this paper, we propose a change detection approach based on nonlinear scale space analysis of change images for robust detection of various changes incurred by natural phenomena and/or humanExpand
Shape-based Image Correspondence
TLDR
This paper investigates the effect of adding shape correspondence constraints either in the form of pair of corresponding contour fragments or pair of closed curves and explores using object proposals as a way of providing shape constraints with encouraging results. Expand
Alignment by Composition
TLDR
An unsupervised method to establish dense semantic correspondences between images depicting different instances of the same object category using objectness, saliency, and visual similarity cues to co-localize the regions of holistic foreground objects. Expand
Subpixel Semantic Flow
TLDR
This paper revisits a classic dense descriptor, namely Geometric Blur, which is, in contrast, extracted from a linear filter response that can be linearized and therefore interpolated at subpixel values, and presents promising results encouraging the use of gradient based continuous optimization in establishing dense semantic correspondences. Expand