Dual-focal Metalens for Long-Range Monocular Depth Estimation

Hyunwoo Son,Taewon Choi,Byoungho LeeTop Scholar

Frontiers in Optics + Laser Science 2022 (FIO, LS)（2022）

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Abstract

A conventional metalens with single focus has limited depth range for monocular depth estimation. To overcome this, we designed dual-focal metalens and learned depth-dependent point spread functions and estimation networks in an end-to-end manner.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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