Abstract: Few-shot object detection (FSOD) aims to detect objects with only a few training examples. Visual feature extraction and query-support similarity learning are the two critical components.
This is the official PyTorch implementation of LLMDet. Recent open-vocabulary detectors achieve promising performance with abundant region-level annotated data. In this work, we show that an ...
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