sfzhang15/RefineDet

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1424 stars · 383 forks observed · 2026-08-28

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

RefineDet is a C++/Caffe implementation of the CVPR 2018 single-shot object detection model that refines anchors to combine one-stage speed with two-stage accuracy. It provides training, evaluation, and pre-trained models for object detection research.

Use cases

• train a single-shot object detection model
• reproduce RefineDet CVPR 2018 results
• evaluate object detectors on VOC and COCO
• compare one-stage vs two-stage detector accuracy
• fine-tune a pre-trained object detection model
• research anchor refinement for detection

When to choose

• you need a research-grade object detector with published CVPR results
• you want to build on or extend a Caffe-based detection pipeline
• you need pre-trained RefineDet models for benchmarking

When to avoid

• you need a maintained framework with recent GPU/CUDA support
• you want PyTorch or TensorFlow tooling
• you need production-ready detection with easy deployment

Facets

library · maturity maintenance

machine-learning computer-vision image-processing computer-vision deep-learning machine-learning cpp python object-detection caffe cvpr-2018 single-shot-detector research-code linux gpu

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