Launch: RF-DETR Keypoint in Roboflow

RF-DETR Keypoint is a real-time, end-to-end pose detection model introduced by Roboflow that surpasses YOLO26-pose in both accuracy and speed while providing calibrated per-keypoint uncertainty from user data. It is designed to seamlessly integrate with Roboflow's platform, allowing users to label, train, and deploy skeleton-based models for various applications such as sports analytics and robot guidance. The model differs from other pose models by predicting a structured set of keypoints in a single forward pass and offering flexibility in defining arbitrary skeletons, not limited to the COCO benchmark. It is trained using weight-sharing neural architecture search, enabling a single set of weights to run across multiple resolutions without retraining. Released under the Apache 2.0 license, RF-DETR Keypoint allows for commercial use without copyleft obligations, addressing licensing barriers that may have previously hindered deployment.