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- W4320341702 abstract "Deep lens optimization has recently emerged as a new paradigm for designing computational imaging systems, however it has been limited to either simple optical systems consisting of a single DOE or metalens, or the fine-tuning of compound lenses from good initial designs. Here we present a deep lens design method based on curriculum learning, which is able to learn optical designs of compound lenses ab initio from randomly initialized surfaces, therefore overcoming the need for a good initial design. We demonstrate this approach with the fully-automatic design of an extended depth-of-field computational camera in a cellphone-style form factor, highly aspherical surfaces, and a short back focal length." @default.
- W4320341702 created "2023-02-13" @default.
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- W4320341702 date "2023-02-02" @default.
- W4320341702 modified "2023-09-23" @default.
- W4320341702 title "Curriculum Learning for ab initio Deep Learned Refractive Optics" @default.
- W4320341702 doi "https://doi.org/10.48550/arxiv.2302.01089" @default.
- W4320341702 hasPublicationYear "2023" @default.
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