Product
Solutions
Resources
Pricing
Docs
Talk to SalesSign in
Models
YOLOX vs. Faster R-CNN

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

YOLOX vs. Faster R-CNN

Both

YOLOX

and

Faster R-CNN

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

YOLOX

and

Faster R-CNN

.

  YOLOX Faster R-CNN
Date of Release Jul 18, 2021
Model Type Object Detection Object Detection
Architecture CNN, YOLO
GitHub Stars 7600 7800

YOLOX

YOLOX is a high-performance object detection model.

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

Faster R-CNN

One of the most accurate object detection algorithms but requires a lot of power at inference time. A good choice if you can do processing asynchronously on a server.

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix
Learn more about YOLOX
Learn more about Faster R-CNN

Compare YOLOX to other models

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

Compare Faster R-CNN 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