SegFormer vs. YOLOR: Compared and Contrasted

Models

SegFormer is a computer vision framework used in semantic segmentation tasks, implemented with transformers.

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

Model Type

Semantic Segmentation

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

Transformers

CNN, YOLO

Annotation Format

Instance Segmentation

Framework

PyTorch

GitHub

GitHub Stars

2.2k+

2k+

License

NVIDIA Source Code

GPL-3.0

Paper

Training Notebook

Deploy Model

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.