Model Card for DiffusionDet

DiffusionDet is a diffusion-based object detection model that formulates object detection as a denoising diffusion process. It iteratively refines noisy box predictions to generate high-quality detection outputs. This approach provides a flexible and unified framework for object detection, offering advantages over traditional proposal-based methods.

🔧 Uses

You can load and use the model with Hugging Face's 🤗 transformers or via the original repository.

• 📦 Original GitHub repo
• 🚀 Few-shot cross-domain adaptation repo

This model has been adapted for cross-domain few-shot object detection using LoRA (Low-Rank Adaptation). 📄 Check out the paper: LoRA for Cross-Domain Few-Shot Object Detection