YOLOv11 vs. Faster R-CNN: Compared and Contrasted

Models

YOLO11

YOLO11 is a computer vision model that you can use for object detection, segmentation, and classification.

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

Frameworks

TensorFlow 1.5

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

29000

7.5k+

License

AGPL-3.0

MIT

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare Alternatives

Compare YOLOv11 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.

YOLOv11 vs. Faster R-CNN

Models

YOLO11

Faster R-CNN

Compare YOLO11 and Faster R-CNN with Autodistill

Compare YOLOv11 vs. Faster R-CNN