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

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare YOLOS vs. Faster R-CNN

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.

YOLOS vs. Faster R-CNN

Models

YOLOS

Faster R-CNN

Compare YOLOS and Faster R-CNN with Autodistill

Compare YOLOS vs. Faster R-CNN