# Zero-shot object detection

LLMDet is a powerful open-vocabulary object detector supervised by large language models, capable of zero-shot object detection.

OWLv2 is a zero-shot text-conditioned object detection model that can detect objects in images through text queries.

OWL-ViT is a zero-shot object detection model based on Vision Transformer, capable of detecting objects of new categories without fine-tuning.

OWLv2 is a zero-shot text-conditioned object detection model that can detect and locate objects in images through text queries.

OWLv2 is a zero-shot text-conditioned object detection model that can detect objects in images through text queries without requiring category-specific training data.

OWLv2 is a zero-shot text-conditioned object detection model that can retrieve objects in images through text queries.

OWLv2 is a zero-shot text-conditioned object detection model that can localize objects in images through text queries.

OWLv2 is a zero-shot text-conditioned object detection model that can retrieve objects in images through text queries.

Grounding DINO is an open-set object detection model that combines the DINO detector with grounding pre-training, enabling zero-shot object detection.

OWL-ViT is a zero-shot text-conditioned object detection model that can search for objects in images via text queries without requiring category-specific training data.