SOURCE-LINKED INTELLIGENCE

Back to the Feature: Zero-Shot 6DoF Pose Estimation via Dense Local Features

arXiv · AI, language, vision and robotics · article · Sep 6, 2026 · UTC

We present B2TFPose, a training-free zero-shot method for 6DoF pose estimation of unseen objects from RGB images. Using a single frozen DINOv3 vision transformer as its only pretrained component within the pose estimation pipeline, B2TFPose extracts dense patch-level features that generalize across the synthetic-to-real domain gap without any task-specific fine-tuning, revisiting the classical local feature matching paradigm through the lens of large-scale self-supervised foundation models. Three contributions advance the training-free state of the art. A geodesic non-maximum suppression strat

Read original source ↗ Open in workspace

recordType

paper

region

Global