Optoelectronic neuromorphic visual sensors have garnered considerable interest owing to their ability to both detect light and perform synaptic computations within a single device. This in‐sensor integration reduces the energy‐intensive data transfer between separate sensing and processing hardware, presenting an energy‐efficient pathway toward bio‐inspired machine vision. However, limited optical absorption in ultrathin photoactive layers can hinder their practical deployment in artificial vision systems. This review examines how resonant photonic structures address this challenge by serving as an additional geometric design dimension that complements active‐material engineering. Recent advancements are organized into three architecture families: plasmonic structures (nanoparticles and periodic patterns), multilayer interference architectures (Fabry–Pérot resonators, distributed Bragg reflectors, and Tamm‐plasmon structures), and nanowire arrays. Depending on the device configuration, photonic geometry and material optical properties jointly control optical field enhancement within the active layer, wavelength selectivity, and polarization sensitivity, whereas multilevel storage relies on material‐ and interface‐level switching mechanisms. This structural engineering supports filter‐free, energy‐efficient, and multispectral in‐sensor computing for next‐generation artificial vision applications.
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Kim et al. (2026) studied this question.
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