MobileNet SSD v2 vs. YOLOR

Both MobileNet SSD v2 and YOLOR are commonly used in computer vision projects. Below, we compare and contrast MobileNet SSD v2 and YOLOR.

Models

This architecture provides good realtime results on limited compute. It's designed to run in realtime (30 frames per second) even on mobile devices.

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

Model Type

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

CNN, YOLO

Annotation Format

Instance Segmentation

Framework

TensorFlow 1.5

PyTorch

GitHub

GitHub Stars

81+

2k+

License

MIT

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.