zhaoweicai/cascade-rcnn

Health v2 · maintenance only

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1061 stars · 289 forks observed · 2026-08-28

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

A C++/Caffe implementation of Cascade R-CNN and other popular two-stage object detection frameworks such as Faster R-CNN, R-FCN, and FPN. It supports training and benchmarking on MS-COCO and PASCAL VOC with multiple backbone networks.

Use cases

• train a Cascade R-CNN object detector on MS-COCO
• reproduce CVPR 2018 Cascade R-CNN paper results
• benchmark Faster R-CNN, R-FCN, and FPN detectors on PASCAL VOC
• implement high-quality object detection that rejects close false positives
• train object detection models with ResNet or VGG backbones in Caffe

When to choose

• you need the original author's Caffe implementation of Cascade R-CNN
• your pipeline is built on Caffe and C++
• you want to reproduce the paper's MS-COCO benchmark numbers

When to avoid

• you prefer a modern PyTorch or TensorFlow implementation (use mmdetection, Detectron, or tensorpack)
• you need Mask R-CNN or instance segmentation support
• you need an actively maintained project with a license

Facets

library · maturity maintenance

computer-vision deep-learning machine-learning image-processing computer-vision deep-learning machine-learning image-processing cpp object-detection cascade-rcnn faster-rcnn caffe coco pascal-voc research-code linux gpu docker

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