AI RESEARCH
6D Pose Estimation via Keypoint Heatmap Regression with RGB-D Residual Neural Networks
arXiv CS.CV
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ArXi:2605.08059v1 Announce Type: new In this paper, we propose a modular framework for 6D pose estimation based on keypoint heatmap regression. Our approach combines YOLOv10m for object detection with a ResNet18-based network that predicts 2D heatmaps from RGB images. Keypoints extracted from these heatmaps are used to estimate the 6D object pose via the PnP RANSAC algorithm. We compare different keypoint selection strategies to assess their impact on pose accuracy.