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Spatiotemporal optical computing devices which could perform mathematical operations in both spatial and temporal domains can provide unprecedented measures to build efficient and real-time information processing systems. It is particularly…
Remote sensing spatiotemporal fusion (STF) addresses the fundamental trade-off between temporal and spatial resolution by combining high temporal-low spatial and high spatial-low temporal imagery. This paper presents the first comprehensive…
Spatiotemporal and motion features are two complementary and crucial information for video action recognition. Recent state-of-the-art methods adopt a 3D CNN stream to learn spatiotemporal features and another flow stream to learn motion…
Multispectral imaging plays a critical role in a range of intelligent transportation applications, including advanced driver assistance systems (ADAS), traffic monitoring, and night vision. However, accurate visible and thermal (RGB-T)…
Metasurfaces are a key photonic platform to manipulate classical light using sub-wavelength structures with designer optical response. Static metasurfaces have recently entered the realm of quantum photonics, showing their ability to tailor…
Metasurfaces offer great potential to control near- and far-fields through engineering of optical properties of elementary cells or meta-atoms. Such perspective opens a route to efficient manipulation of the optical signals both at…
Metasurfaces have achieved fruitful results in tailoring complexing light fields in free space. However, a systematic investigation on applying the concept of meta-optics to completely control waveguide modes is still elusive. Here we…
Multi-object tracking (MOT) has profound applications in a variety of fields, including surveillance, sports analytics, self-driving, and cooperative robotics. Despite considerable advancements, existing MOT methodologies tend to falter…
Geometrical singularities in plasmonic metasurfaces have recently been proposed for the enhancement of light-matter interactions, owing to their broadband light-harvesting properties and extreme plasmon confinement. However, the large…
Spatiotemporal (ST) learning has become a crucial technique to enable smart cities and sustainable urban development. Current ST learning models capture the heterogeneity via various spatial convolution and temporal evolution blocks.…
We extend effective medium theory (EMT) to time-modulated, frequency-dispersive acoustic metamaterials with multiple resonances. While previous studies focused on non-dispersive or single-resonance systems, advances in programmable…
Time-varying photonic systems open new possibilities for controlling light, enabling photonic time crystals, time reflection and refraction, frequency conversion, synthetic gauge fields, optical nonreciprocity, among others. These effects…
Nonreciprocal nonhermitian systems provide an unconventional localization mechanism of topological zero modes via the nonhermitian skin effect. While fundamental theoretical characterizations of this effect involve the biorthogonal system…
Surface lattice resonance supported on plasmonic nanoparticle arrays enhances light-matter interactions for applications such as photoluminescence enhancement. The photoluminescence process is enhanced through confining light beyond the…
Topological modes (TMs) are typically localized at boundaries, interfaces and dislocations, and exponentially decay into the bulk of a large enough lattice. Recently, the non-Hermitian skin effect has been leveraged to delocalize the…
We extend the density-functional theory for superconductors (SCDFT) to take account of the dynamical structure of the screened Coulomb interaction. We construct an exchange-correlation kernel in the SCDFT gap equation on the basis of the…
In this paper, we experimentally demonstrate a non-Hermitian open PT-symmetric terahertz metasurface comprising complementary plasmonic structures capable of exhibiting an exceptional point (EP). The metasurface consists of two resonators…
Forecasting complex time series is an important yet challenging problem that involves various industrial applications. Recently, masked time-series modeling has been proposed to effectively model temporal dependencies for forecasting by…
Multivariate Time-Series (MTS) data is crucial in various application fields. With its sequential and multi-source (multiple sensors) properties, MTS data inherently exhibits Spatial-Temporal (ST) dependencies, involving temporal…
Non-Hermitian topological matter provides a platform for engineering phenomena that go beyond the capabilities of Hermitian systems, enabling the use of losses to engineer topological phenomena. Non-Hermitian models often rely on artificial…