YOLOv8 Instance Segmentation vs. YOLOR

Both YOLOv8 Instance Segmentation and YOLOR are commonly used in computer vision projects. Below, we compare and contrast YOLOv8 Instance Segmentation and YOLOR.

Models

YOLOv8 Instance Segmentation

The state-of-the-art YOLOv8 model comes with support for instance segmentation tasks.

Learn more about YOLOv8 Instance Segmentation

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

Model Type

Instance Segmentation

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO

CNN, YOLO

Frameworks

PyTorch

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

21.1k+

2k+

License

AGPL-3.0

GPL-3.0

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare YOLOv8 Instance Segmentation vs. YOLOR

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.

YOLOv8 Instance Segmentation vs. YOLOR

Models