What is the different between SSD and SSD Lite ??(Tensorflow)

Question

I've read the paper MobileNetV2(arXiv:1801.04381)

and ran the model from Tensorflow model zoo.

I noticed that the inference time of SSD Lite MobileNetV2 is faster than SSD MobileNetV2.

At the MobileNetV2 paper, there is only a short explanation about SSD Lite in the following sentence:

'We replace all the regular convolutions with separable convolutions (depthwise followed by 1 × 1 projection) in SSD prediction layers'.

So my question is, what is the difference between SSD and SSD Lite?

I don't understand the difference because when the MobileNetV1(arXiv:1704.04861v1) was published and applied to SSD, it has already replaced all the convolutional layers to depthwise separable convolutions that were mentioned above.

Answer 1

It is frustrating since all searches for SSDLite result in "a novel framework we call SSDLite" so I was expecting a thing. However, I suspect that SSDLite is simply implemented by one modification (kernel_size) and two additions (use_depthwise) to the common SSD model file.

Comparing the model files ssd_mobilenet_v1_coco.config and sdlite_mobilenet_v2_coco.config produces the following:

model {
  ssd {
    box_predictor {
      convolutional_box_predictor {
        kernel_size: 3
        use_depthwise: true
      }
    }
    feature_extractor {
      use_depthwise: true
    }
  }
}

I'll have to try it out.

Answer 2

As one of the answer already pointed out, the main differences in configs were the two use_depthwise options for both box_predictor and feature_extractor. The underlying changes had already been implemented in the codebase which essentially replace all regular convolutions in SSD layers and the last box+class prediction layer to depthwise + pointwise separable convolutions. The theoretical parameter and flops saving were described in our MobilenetV2 paper.

Also to answer the question of @Seongkyun Han, we did not replace all the conv in SSD layers in our v1 paper (only all the layers that belong to mobilenet were separable conv).