P$^3$OVD: Fine-grained Visual-Text Prompt-Driven Self-Training for Open-Vocabulary Object Detection. (arXiv:2211.00849v1 [cs.CV])

Inspired by the success of visual-language methods (VLMs) in zero-shot
classification, recent works attempt to extend this line of work into object
detection by leveraging the localization ability of pre-trained VLMs and
generating pseudo labels for unseen classes in a self-training manner. However,
since the current VLMs are usually pre-trained with aligning sentence embedding
with global image embedding, the direct use of them lacks fine-grained
alignment for object instances, which is the core of detection. In this paper,
we propose …

arxiv detection fine-grained self-training text training