Model Overview

Mask R-CNN is a convolution based network for object instance segmentation.

Model Architecture

Mask R-CNN builds on top of Faster R-CNN adding a mask head for the task of image segmentation.

The architecture consists of the following:

ResNet-50 backbone with Feature Pyramid Network (FPN)
Region proposal network (RPN) head
RoI Align
Bounding and classification box head
Mask head

$\"Architecture\"$

Figure 1. Diagram of Mask R-CNN framework from original paper

Training

This model was trained using script available on NGC and in GitHub repo

Dataset

The following datasets were used to train this model:

COCO 2017 - Dataset for large-scale object detection, segmentation and captioning.

Performance

Performance numbers for this model are available in NGC

References

License

This model was trained using open-source software available in Deep Learning Examples repository.\nFor terms of use, please refer to the license of the script and the datasets the model was derived from.

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Diagram of Mask R-CNN framework from [original paper](https://arxiv.org/abs/1703.06870)\n\n\n \n## Training\n\nThis model was trained using script available on [NGC](https://ngc.nvidia.com/catalog/resources/nvidia:mask_r_cnn_for_tensorflow2) and in [GitHub repo](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN)\n\n## Dataset\n\nThe following datasets were used to train this model:\n- [COCO 2017](https://cocodataset.org/#download) - Dataset for large-scale object detection, segmentation and captioning.\n\n\n## Performance\n\nPerformance numbers for this model are available in [NGC](https://ngc.nvidia.com/catalog/resources/nvidia:mask_r_cnn_for_tensorflow2/performance)\n\n## References\n- [original paper](https://arxiv.org/abs/1703.06870)\n- [NVIDIA model implementation in NGC](https://ngc.nvidia.com/catalog/resources/nvidia:mask_r_cnn_for_tensorflow2)\n- [NVIDIA model implementation on GitHub](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN)\n\n## License\n\nThis model was trained using open-source software available in [Deep Learning Examples](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN) repository.\nFor terms of use, please refer to the license of the script and the datasets the model was derived from.","displayName","Mask R-CNN TensorFlow checkpoint (AMP)",["D",1680637127185],"publisher","NVIDIA Deep Learning Examples","latestVersion","collectionCounts","imageUrl","/api/image/nvidia/-/models/maskrcnn_tf1_amp_ckpt","rawImageUrl","https://assets.nvidiagrid.net/ngc/logos/Deep-Learning-Examples.png","canGuestDownload","latestVersionSizeInBytes","licenseTerms","isMultinodeEnabled","isMultiArchitecture","bias","explainability","privacy","safetyAndSecurity","featureLabels",[],"displayLabels",[278,279],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_247":288,"_115":289,"_282":290,"_284":285},{"_247":280,"_115":281,"_282":283,"_284":285},"Deep Learning Examples","pltfm_deep_learning_examples","filter",{"_286":287,"_115":281},"category","label","field","platform","Computer Vision","soln_computer_vision",{"_286":291,"_115":289},"technology",{"_160":1270,"_162":1271},"ngcApps",[1223],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1204":1205,"_1206":1207,"_1208":1209,"_1210":1211,"_1212":303,"_191":327,"_1213":1214,"_1215":59,"_1216":139,"_1217":139,"_1218":1219,"_1220":139,"_1221":1222},"amplitude",{"_1201":1202,"_838":-7,"_1203":34},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMSUyMiUzQXRydWUlN0Q=","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1195":1196,"_1197":1198,"_1199":1200},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.10.0","defaultSearchSuggestions",{"_1078":220,"_1079":1080,"_1081":1082,"_1083":1084},"announcements",[],"consentState",{"_365":1068,"_1069":34,"_1070":34,"_1071":139,"_1072":1073},"consentConfig",{"_347":348,"_349":350,"_351":352,"_353":354,"_355":356,"_357":358,"_359":360,"_361":362,"_363":364,"_365":366},"showContactAdmin",1785122919492,[],[],[341,342,343,344,345,346],{"_48":63,"_50":74,"_52":155,"_54":-5,"_56":-5,"_58":59},{"_48":63,"_50":70,"_52":155,"_54":-5,"_56":-5,"_58":59},{"_48":63,"_50":68,"_52":155,"_54":-5,"_56":-5,"_58":59},{"_48":63,"_50":64,"_52":155,"_54":-5,"_56":-5,"_58":59},{"_48":60,"_50":61,"_52":155,"_54":-5,"_56":-5,"_58":59},{"_48":49,"_50":51,"_52":155,"_54":-5,"_56":-5,"_58":59},"mainInfoText","We and our third-party partners (including social media, advertising, and analytics partners) use cookies and other tracking technologies to collect, store, monitor, and process certain information about you when you visit our website. 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users logged in across NVIDIA domains.","api.ngc.nvidia.com","This cookie is managed by AWS and is used for load balancing.","bm_so","This cookie name is used to load the site as quickly as possible and to recognize bots using Akamai.","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. 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It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","This cookie is associated with Akamai and is used to differentiate between traffic from humans and bots.","nv_co","__uxq412__ses.88c1","learn.learn.nvidia.com","This cookie is associated with the Amazon Web Services Elastic Load Balancing functionality for routing client request on the server.","pctrk","Used to count page views by unauthenticated users against license usage.","bm_s","bpazaws52gukakzc__ctrl0_ctl36_uccaptcha","bm_sv","store.nvidia.com","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. 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Key	Value
batch_size	4
dataset	COCO2017
iterations	45000
learning_rate	0.04
training_precision	AMP

Key	Value
box_AP	0.376031935
mask_AP	0.340773255