YOLOS vs. Faster R-CNN: Compared and Contrasted

Models

YOLOS

YOLOS looks at patches of an image to to form "patch tokens", which are used in place of the traditional wordpiece tokens in NLP.

Learn more about YOLOS

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

Transformer, YOLO

Frameworks

PyTorch

TensorFlow 1.5

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

812+

7.5k+

License

MIT

Paper

Training Notebook

Deploy Model

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YOLOS vs. Faster R-CNN

Both

YOLOS

and

Faster R-CNN

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

YOLOS

and

Faster R-CNN

	YOLOS	Faster R-CNN
Date of Release	Jun 01, 2021
Model Type	Object Detection	Object Detection
Architecture	Transformer, YOLO
GitHub Stars	812	7500

YOLOS

YOLOS looks at patches of an image to to form "patch tokens", which are used in place of the traditional wordpiece tokens in NLP.

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 YOLOS

Learn more about Faster R-CNN