Difference between SSD MobileNet, EfficientNet and Faster R-CNN ResNet 50

3 min readMay 25, 2023

What is the major difference between the 3 popular object detection models?

SSD MobileNet V2, Faster R-CNN ResNet-50, and EfficientDet 4 are all popular object detection models used in computer vision tasks. Each model has its own architecture and characteristics, which result in differences in terms of performance, accuracy, and efficiency.

SSD MobileNet V2 320x320:

SSD (Single Shot MultiBox Detector) is a real-time object detection framework that combines the speed of single-shot detection and accuracy of multi-stage detection.
MobileNet V2 is a lightweight convolutional neural network architecture designed for mobile and embedded devices.
The “320x320” refers to the input image size that the model expects.
SSD MobileNet V2 320x320 provides a good balance between speed and accuracy, making it suitable for real-time applications on resource-constrained devices.

Faster R-CNN ResNet-50:

Faster R-CNN (Region-based Convolutional Neural Networks) is a two-stage object detection framework.
ResNet-50 is a deep convolutional neural network architecture that has 50 layers and is known for its strong performance.
Faster R-CNN uses a region proposal network (RPN) to generate region proposals and then classifies and refines them using a classifier and a regressor.
This model typically offers higher accuracy than SSD but is slower due to the two-stage architecture. It is commonly used when accuracy is a priority over real-time performance.

EfficientDet 4:

EfficientDet is a family of object detection models that are efficient and accurate.
EfficientDet 4 is a specific variant within the EfficientDet series.
It is based on the EfficientNet architecture, which uses compound scaling to achieve a good balance between accuracy and efficiency.
EfficientDet models use a single-stage detection framework similar to SSD but incorporate additional techniques to improve accuracy and efficiency.
EfficientDet 4 generally provides better accuracy than SSD MobileNet V2 while maintaining competitive inference speeds.

In summary, SSD MobileNet V2 is a lightweight real-time object detection model suitable for resource-constrained devices. Faster R-CNN ResNet-50 offers higher accuracy at the expense of speed and is commonly used when accuracy is paramount. EfficientDet 4 is an efficient and accurate object detection model that strikes a balance between accuracy and efficiency. The choice of model depends on the specific requirements of the application, such as the available computational resources, desired accuracy, and real-time performance constraints.

SSD MobileNet V2 320x320