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Llmdet Swin Base Hf
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Llmdet Swin Base Hf

Developed by fushh7
LLMDet is an open-vocabulary object detector supervised by large language models, capable of zero-shot object detection.
Object Detection
Safetensors
Open Source License:Apache-2.0#Zero-shot Object Detection#Open-vocabulary Recognition#Large Language Model Supervision
Downloads 605
Release Time : 4/6/2025

Model Overview

LLMDet is a highlight paper model published at CVPR2025, achieving powerful open-vocabulary object detection capabilities through large language model supervision, particularly suitable for zero-shot object detection tasks.

Model Features

Open-vocabulary Object Detection
Capable of detecting unseen categories in training data, achieving zero-shot learning.
Large Language Model Supervision
Leverages the semantic understanding capabilities of large language models to enhance object detection performance.
Zero-shot Capability
Detects new category objects without requiring training data for specific categories.

Model Capabilities

Zero-shot Object Detection
Open-vocabulary Recognition
Multi-category Object Detection

Use Cases

Computer Vision
Unknown Object Detection
Detects object categories not present in training data within unknown scenarios.
Accurately identifies and localizes unseen objects.
Open-world Object Detection
Detects various objects in open environments without pre-defining all categories.
Enhances the flexibility and adaptability of detection systems.
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