Detectron is Facebook AI Research’s (FAIR) software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning framework.

At FAIR, Detectron has enabled numerous research projects, including: Feature Pyramid Networks for Object DetectionMask R-CNNDetecting and Recognizing Human-Object InteractionsFocal Loss for Dense Object DetectionNon-local Neural NetworksLearning to Segment Every Thing, and Data Distillation: Towards Omni-Supervised Learning.


The goal of Detectron is to provide a high-quality, high-performance codebase for object detection research. It is designed to be flexible in order to support rapid implementation and evaluation of novel research. Detectron includes implementations of the following object detection algorithms:

using the following backbone network architectures:

Additional backbone architectures may be easily implemented. For more details about these models, please see References below.