Open Vocabulary Object Detection with Proposal Mining and Prediction Equalization. (arXiv:2206.11134v2 [cs.CV] UPDATED)

Open-vocabulary object detection (OVD) aims to scale up vocabulary size to
detect objects of novel categories beyond the training vocabulary. Recent work
resorts to the rich knowledge in pre-trained vision-language models. However,
existing methods are ineffective in proposal-level vision-language alignment.
Meanwhile, the models usually suffer from confidence bias toward base
categories and perform worse on novel ones. To overcome the challenges, we
present MEDet, a novel and effective OVD framework with proposal mining and
prediction equalization. First, we design an …

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