SparseR-CNN is a computer vision model that performs object detection in an end-to-end manner by replacing dense region proposal networks with a set of learnable sparse proposals. The model achieves competitive results on COCO benchmark (up to 46.4 box AP) using backbones like ResNet and PVT. It is built on top of a PyTorch-based detection framework with configurable training schedules.