Marrying NeRF with Feature Matching for One-step Pose Estimation

arXiv:2404.00891v1 Announce Type: new
Abstract: Given the image collection of an object, we aim at building a real-time image-based pose estimation method, which requires neither its CAD model nor hours of object-specific training. Recent NeRF-based methods provide a promising solution by directly optimizing the pose from pixel loss between rendered and target images. However, during inference, they require long converging time, and suffer from local minima, making them impractical for real-time robot applications. We aim at solving this problem by …

abstract aim arxiv building cad collection cs.cv cs.ro feature image loss nerf object pixel real-time solution training type