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arXiv Computer Vision By Bingxuan Li, Jiahao Wu, Yuan Xu, Zezheng Zhu, Yunxiang Zhang, Kenneth Chen, Yanqi Liang, Nanfang Yu, Qi Sun

Physically Grounded Monocular Depth via Nanophotonic Wavefront Encoding

Read the original on arXiv Computer Vision →

The paper proposes using ultrathin metalenses to physically encode metric depth cues into two polarized optical wavefronts, enabling accurate monocular depth estimation. By aligning a pretrained depth foundation model with these optical signals through direct fine‑tuning, and by creating a simulation pipeline to generate realistic metalens responses from RGB‑D data, the authors bridge the gap between nanophotonics and learned depth priors. Experiments show that this method surpasses conventional monocular metric depth estimation and depth‑from‑defocus baselines.

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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