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Driven by rapid advances in large-scale generative models, synthetic data has emerged as a promising solution for visual understanding. While modern diffusion models achieve remarkable photorealistic image synthesis, their potential in…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Jinjin Zhang , Xiefan Guo , Yizhou Jin , Nan Zhou , Di Huang

The engineering of the optical response of materials is a paradigm that demands microscopic-level accuracy and reliable predictive theoretical tools. Here we compare and contrast the dispersive permittivity tensor, using both a low-energy…

Materials Science · Physics 2021-09-29 Mohammad Alidoust , Erlend E. Isachsen , Klaus Halterman , Jaakko Akola

Diffusion (score-based) generative models have been widely used for modeling various types of complex data, including images, audios, and point clouds. Recently, the deep connection between forward-backward stochastic differential equations…

Machine Learning · Computer Science 2022-06-22 Weitao Du , Tao Yang , He Zhang , Yuanqi Du

Probabilistic Diffusion Models (PDMs) have recently emerged as a very promising class of generative models, achieving high performance in natural image generation. However, their performance relative to non-natural images, like radar-based…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Alexandre Tuel , Thomas Kerdreux , Claudia Hulbert , Bertrand Rouet-Leduc

Aberrations limit scanning fluorescence microscopy when imaging in scattering materials such as biological tissue. Model-based approaches for adaptive optics take advantage of a computational model of the optical setup. Such models can be…

Optics · Physics 2021-07-07 Ivan Vishniakou , Johannes D. Seelig

Despite diffusion models' superior capabilities in modeling complex distributions, there are still non-trivial distributional discrepancies between generated and ground-truth images, which has resulted in several notable problems in image…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Yujian Liu , Yang Zhang , Tommi Jaakkola , Shiyu Chang

Recent advances in generative modeling, namely Diffusion models, have revolutionized generative modeling, enabling high-quality image generation tailored to user needs. This paper proposes a framework for the generative design of structural…

Diffractive surfaces shape optical wavefronts for applications in spectroscopy, high-speed communication, and imaging. The performance of these structures is primarily determined by how precisely they can be patterned. Fabrication…

Thin structured surfaces allow flexible control over propagation of electromagnetic waves. Focusing and polarization state analysis are among functions, required for effective manipulation of radiation. Here a polarization sensitive Fresnel…

Optics · Physics 2018-05-23 Hen Markovich , Dmitrii Filonov , Ivan Shishkin , Pavel Ginzburg

Imaging systems are inherently prone to aberrations. We present an optimization method to design two-dimensional freeform reflectors that minimize aberrations for various parallel ray beams incident on the optical system. We iteratively…

We present simulations of an efficient high numerical aperture solid immersion metalens concept for fluorescence microscopy. The technique exploits the preferential emission of interfacial dipoles into a high refractive index substrate…

Optics · Physics 2022-01-12 Zhiheng Li , Zequan Chen , Rupert F. Oulton , Ming Fu

Diffusion models generate new samples by progressively decreasing the noise from the initially provided random distribution. This inference procedure generally utilizes a trained neural network numerous times to obtain the final output,…

Most research on astrophysical lensing has been conducted using the geometric optics framework, where there exists a clear concept of lensing images. However, wave optics effects can be important for coherent sources, e.g. pulsars, fast…

Instrumentation and Methods for Astrophysics · Physics 2024-10-29 Xun Shi

Achromatic combinations of a diffractive Phase Fresnel Lens and a refractive correcting element have been proposed for X-ray and gamma-ray astronomy and for microlithography, but considerations of absorption often dictate that the…

Astrophysics · Physics 2009-11-10 Gerald K. Skinner

We describe the change of the spatial distribution of the state of polarisation occurring during two-dimensional imaging through a multilayer and in particular through a layered metallic flat lens. Linear or circular polarisation of…

A rigorous method of calculating the electromagnetic field, the scattering matrix, and scattering cross-sections of an arbitrary finite three-dimensional optical system described by its permittivity distribution is presented. The method is…

Optics · Physics 2018-09-26 S. V. Lobanov , W. Langbein , E. A. Muljarov

Score-based diffusion models achieve state-of-the-art performance for inverse problems, but their practical deployment is hindered by long inference times and cumbersome hyperparameter tuning. While pretrained diffusion models can be reused…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Julio Oscanoa , Irmak Sivgin , Cagan Alkan , Daniel Ennis , John Pauly , Mert Pilanci , Shreyas Vasanawala

Interferometry provides one of the possible routes to ultra-high angular resolution for X-ray and gamma-ray astronomy. Sub-micro-arc-second angular resolution, necessary to achieve objectives such as imaging the regions around the event…

Instrumentation and Methods for Astrophysics · Physics 2009-07-31 G. K. Skinner , J. F. Krizmanic

The photon density operator function is used to calculate light beam propagation through turbulent atmosphere. A kinetic equation for the photon distribution function is derived and solved using the method of characteristics. Optical wave…

Quantum Physics · Physics 2009-11-13 G. P. Berman , A. A. Chumak

In this paper, we argue that iterative computation with diffusion models offers a powerful paradigm for not only generation but also visual perception tasks. We unify tasks such as depth estimation, optical flow, and amodal segmentation…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Rahul Ravishankar , Zeeshan Patel , Jathushan Rajasegaran , Jitendra Malik
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