Yolov3 is about a year old and is still state of the art for all meaningful purposes. It's fast and works well. You might get "better" results with a Faster RCNN variant, but it's slow and the difference will likely be imperceptible. Using map50 as pjreddie points out, isn't a great metric for object detection.

Interestingly in our production systems yolo object detection speed was much faster and accurate.

recommendations for similarly easy but better/more "modern" alternatives?

See Faster-RCNN, R-FCN, SSD, etc

I've ignored mask RCNN becuase it's significantly more time consuming to label your data.

The main candidates are all found in Facebook’s Detectron package, but they didn't feel it necessary to document anything in any significant level of detail: https://github.com/facebookresearch/Detectron

You can see also: https://paperswithcode.com/sota/object-detection-coco