ShoufaChen/DiffusionDet

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

2257 stars · 184 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PyTorch implementation of DiffusionDet, the first diffusion-model-based object detection framework (ICCV 2023 Best Paper Finalist). It provides pretrained models on COCO and LVIS with configurable backbones like ResNet and Swin Transformer.

Use cases

• detect objects in images using a diffusion model
• run object detection with a variable number of denoising steps
• reproduce ICCV 2023 DiffusionDet paper results on COCO and LVIS
• fine-tune a diffusion-based object detector on custom datasets
• compare diffusion-based detection against DETR-style detectors
• use pretrained ResNet or Swin backbone detection models

When to choose

• you want to experiment with diffusion models for object detection
• you need a research baseline for diffusion-based detection
• you want flexible inference with adjustable denoising steps trading speed for accuracy

When to avoid

• you need a production-ready, actively maintained detector
• you need real-time detection at high frame rates
• you require a permissive commercial license (CC-BY-NC 4.0 restricts commercial use)

Facets

library · maturity maintenance

machine-learning deep-learning computer-vision image-processing computer-vision deep-learning machine-learning artificial-intelligence python object-detection diffusion-model pytorch research-code iccv2023 coco lvis linux gpu

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