iNeRF: Inverting Neural Radiance Fields for Pose Estimation
Yen-Chen Lin, Pete Florence, Jonathan T. Barron et al.
2021 · 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · 392 citations
We present iNeRF, a framework that performs mesh-free pose estimation by "inverting" a Neural Radiance Field (NeRF). NeRFs have been shown to be remarkably effective for the task of view synthesis — synthesizing photorealistic novel views of real-world scenes or objects. In this work, we investigate whether we can apply analysis-by-synthesis via NeRF for mesh-free, RGB-only 6DoF pose estimation – given an image, find the translation and rotation of a camera relative to a 3D object or scene. Our method assumes that no object mesh models are available during either training or test time. Starti…
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