This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.
It's an excellent job in the repo.
For computer vision, some of the tasks will be important. I will provide some topics and references that I am familiar with.
Instance Segmentation: MASK-RCNN The dataset used for evaluation is COCO
Bounding-Box Object Detection MASK-RCNN
Some other metrics for evaluation might be important, such as fps for detection. YOLO2 SSD
For bounding-box object detection, there are some other datasets: ImageNet DET Pascal VOC UA-DETRAC
I have not looked at the development in speed for a while, so might be something new. MASK-RCNN provides the best accuracy now for sure.