YOLOR vs. Faster R-CNN: Compared and Contrasted

Models

YOLOR

YOLOR (You Only Learn One Representation) is an object detection model that uses both implicit and explicit knowledge to make predictions.

Learn more about YOLOR

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.

Learn more about Faster R-CNN

Model Type

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

CNN, YOLO

Frameworks

PyTorch

TensorFlow 1.5

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

2k+

7.5k+

License

GPL-3.0

MIT

Paper

Training Notebook

Deploy Model

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YOLOR vs. Faster R-CNN

Both

YOLOR

and

Faster R-CNN

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

YOLOR

and

Faster R-CNN

	YOLOR	Faster R-CNN
Date of Release	May 10, 2021
Model Type	Object Detection	Object Detection
Architecture	CNN, YOLO
GitHub Stars	2000	7500

YOLOR

YOLOR (You Only Learn One Representation) is an object detection model that uses both implicit and explicit knowledge to make predictions.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How 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 Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix

Learn more about YOLOR

Learn more about Faster R-CNN