title: What is the different between SSD and SSD Lite ??(Tensorflow)
body: <p>I've read the paper MobileNetV2(arXiv:1801.04381)</p>
  
  <p>and ran the model from <a href="https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md" rel="noreferrer">Tensorflow model zoo</a>.</p>
  
  <p>I noticed that the inference time of SSD Lite MobileNetV2 is faster than SSD MobileNetV2.</p>
  
  <p>At the MobileNetV2 paper, there is only a short explanation about SSD Lite in the following sentence:</p>
  
  <p>'We replace all the regular convolutions with separable convolutions (depthwise
  followed by 1 × 1 projection) in SSD prediction layers'.</p>
  
  <p>So my question is, what is the difference between SSD and SSD Lite?</p>
  
  <p>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.</p>