What is the fastest Mask R-CNN implementation available
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.

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.

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

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

It's almost impossible to get higher inference speed for Mask R-CNN on GTX 1080. You may check detectron2 by Facebook AI Research.
Otherwise, I'd suggest to use YOLACT - (You Only Look At CoefficienTs), it can achieve real-time instance segmentation.

On the other hand, if you don't need instance segmentation, you can use YOLO, SSD, etc for object detection.
