<p>As @kkHarshit already mentioned it is very hard to speed up a Mask R-CNN any further.</p>
<p>The fastest instance segmentation model that I found is <a href="https://arxiv.org/abs/2012.12259" rel="nofollow noreferrer">YolactEdge: Real-time Instance Segmentation on the Edge (Jetson AGX Xavier: 30 FPS, RTX 2080 Ti: 170 FPS)</a>.</p>
<p>It's perfomance is worse than Mask R-CNN or Yolact even but still very good.</p>
What is the fastest Mask R-CNN implementation available
<p>I'm running a Mask R-CNN model on an edge device (with an NVIDIA GTX 1080). I am currently using the Detectron2 Mask R-CNN implementation and I archieve an inference speed of around 5 FPS.</p>

<p>To speed this up I looked at other inference engines and model implementations. For example ONNX, but I'm not able to gain a faster inference speed.</p>

<p>TensorRT looks very promising to me but I did not found a ready "out-of-the-box" implementation for it. </p>

<p>Are there any other mature and fast inference engines or other techniques to speed up the inference?</p>