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Zero-Shot Object Detection by Hybrid Region Embedding
[article]
2018
arXiv
pre-print
Object detection is considered as one of the most challenging problems in computer vision, since it requires correct prediction of both classes and locations of objects in images. In this study, we define a more difficult scenario, namely zero-shot object detection (ZSD) where no visual training data is available for some of the target object classes. We present a novel approach to tackle this ZSD problem, where a convex combination of embeddings are used in conjunction with a detection
arXiv:1805.06157v2
fatcat:34tfhvllxbaoddgrah4hefxzsq