Product
Solutions
Resources
Pricing
Docs
Talk to SalesSign in
Models
Mask RCNN vs. YOLOv3 PyTorch

Explore Models

By Task
All Models (32)Object Detection Models (19)Classification Models (7)Instance Segmentation Models (3)Semantic Segmentation Models (1)
By Feature
Foundation Vision ModelsMultimodal Vision ModelsImage Embedding ModelsReal Time Vision ModelsZero-Shot Detection ModelsOptimal for Edge Deployment

Mask RCNN vs. YOLOv3 PyTorch

Both

Mask RCNN

and

YOLOv3 PyTorch

are commonly used in computer vision projects. Below, we compare and contrast

Mask RCNN

and

YOLOv3 PyTorch

.

  Mask RCNN YOLOv3 PyTorch
Date of Release Oct 23, 2017 Apr 08, 2018
Model Type Instance Segmentation Object Detection
Architecture YOLO
GitHub Stars 22500 6800

Mask RCNN

Mask RCNN is a convolutional neural network for instance segmentation.

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix

YOLOv3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix
Learn more about Mask RCNN
Learn more about YOLOv3 PyTorch

Compare Mask RCNN to other models

MobileNet V2 Classification
MobileNet SSD v2
YOLOv3 Keras
YOLOv3 PyTorch
YOLOv4 PyTorch

Compare YOLOv3 PyTorch to other models

YOLOv8 Instance Segmentation
YOLOv8
YOLOv7 Instance Segmentation
OneFormer
MobileNet V2 Classification

Deploy a computer vision model today

Join 250,000 developers curating high quality datasets and deploying better models with Roboflow.

Get started