SegFormer vs. Faster R-CNN

Both SegFormer and Faster R-CNN are commonly used in computer vision projects. Below, we compare and contrast SegFormer and Faster R-CNN.

Models

SegFormer

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

Learn more about SegFormer

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

Semantic Segmentation

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

Transformers

Frameworks

PyTorch

TensorFlow 1.5

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

2.2k+

7.5k+

License

NVIDIA Source Code

MIT

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare SegFormer 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.

SegFormer vs. Faster R-CNN

Models

SegFormer

Faster R-CNN

Compare SegFormer and Faster R-CNN with Autodistill

Compare SegFormer vs. Faster R-CNN