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Found 3 papers, 2 papers with code
Fast One-Stage Unsupervised Domain Adaptive Person Search
Unsupervised person search aims to localize a particular target person from a gallery set of scene images without annotations, which is extremely challenging due to the unexpected variations of the unlabeled domains.
Learning to predict crisp boundaries
Recent methods for boundary or edge detection built on Deep Convolutional Neural Networks (CNNs) typically suffer from the issue of predicted edges being thick and need post-processing to obtain crisp boundaries.
Relative Depth Order Estimation Using Multi-scale Densely Connected Convolutional Networks
We study the problem of estimating the relative depth order of point pairs in a monocular image.
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