Toward Open Vocabulary Aerial Object Detection with CLIP-Activated Student-Teacher Learning

arXiv:2311.11646v2 Announce Type: replace
Abstract: An increasingly massive number of remote-sensing images spurs the development of extensible object detectors that can detect objects beyond training categories without costly collecting new labeled data. In this paper, we aim to develop open-vocabulary object detection (OVD) technique in aerial images that scales up object vocabulary size beyond training data. The fundamental challenges hinder open vocabulary object detection performance: the qualities of the class-agnostic region proposals and the pseudo-labels that can generalize well to …

abstract aerial aim arxiv beyond clip cs.cv data detection development images massive object objects paper remote-sensing sensing training type