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arXiv Computer Vision By Yesheng Zhang, Xiang Dai, Xu Zhao, Chongyang Zhang

NaCR: Visual Localization via NeRF-aided Camera Ray Regression

Read the original on arXiv Computer Vision →

NaCR: Visual Localization via NeRF-aided Camera Ray Regression proposes a unified framework that integrates Neural Radiance Fields (NeRF) with Camera Ray Regression (CRR) to improve visual localization accuracy. The method enhances the CRR baseline with three simple improvements, augments training data by synthesizing novel views from a pre‑trained NeRF, and employs a closed‑loop supervision pipeline that back‑propagates photometric rendering errors to refine predicted camera rays. A two‑stage training curriculum ensures stable convergence, and experiments on indoor and outdoor benchmarks show competitive accuracy with validated component efficacy.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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