# Open-vocabulary Recognition

LLMDet is a powerful open-vocabulary object detector supervised by large language models, a highlight paper at CVPR2025

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

YOLOE is a real-time visual omni-model that combines object detection and visual understanding capabilities, suitable for various visual tasks.

GenMedClip is a zero-shot image classification model based on the open_clip library, specializing in medical image analysis.

EVA02 CLIP is a large-scale vision-language model based on the CLIP architecture, supporting tasks such as zero-shot image classification.

OmDet-Turbo is an efficient fusion-head open-vocabulary detection model based on real-time Transformer, suitable for zero-shot object detection tasks.

CLIP model based on the ResNet50x64 architecture from the OpenCLIP library, supporting zero-shot image classification tasks.

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

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

A vision-language model based on the CLIP architecture, supporting zero-shot image classification tasks

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

OWL-ViT is a zero-shot text-conditioned object detection model that can detect objects in images via text queries.