Grid R-CNN
Grid R-CNN
**Grid R-CNN** is an object detection framework, where the traditional regression
formulation is replaced by a grid point guided localization mechanism.

Grid R-CNN divides the object bounding box region into grids and employs a fully convolutional network ([FCN](https://paperswithcode.com/method/fcn)) to predict the locations of grid points. Owing to the position sensitive property of fully convolutional architecture, Grid R-CNN maintains the explicit spatial information and grid points locations can be obtained in pixel level. When a certain number of grid points at specified location are known, the corresponding bounding box is definitely determined. Guided by the grid points, Grid R-CNN can determine more accurate object bounding box than regression method which lacks the guidance of explicit spatial information.
Grid R-CNN
https://paperswithcode.com/paper/grid-r-cnn
Grid R-CNN