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Progressive Flow-inspired Unfolding for Spectral Compressive Imaging
Xiaodong Wang, Ping Wang, Zijun He +2
Coded aperture snapshot spectral imaging (CASSI) retrieves a 3D hyperspectral image (HSI) from a single 2D compressed measurement, which is a highly challenging reconstruction task…
Plug-and-play Diffusion Models for Image Compressive Sensing with Data Consistency Projection
Xiaodong Wang, Ping Wang, Zhangyuan Li +1
We explore the connection between Plug-and-Play (PnP) methods and Denoising Diffusion Implicit Models (DDIM) for solving ill-posed inverse problems, with a focus on single-pixel im…
Texture-aware Intrinsic Image Decomposition with Model- and Learning-based Priors
Xiaodong Wang, Zijun He, Xin Yuan
This paper aims to recover the intrinsic reflectance layer and shading layer given a single image. Though this intrinsic image decomposition problem has been studied for decades, i…
Spectral Compressive Imaging via Chromaticity-Intensity Decomposition
Xiaodong Wang, Zijun He, Ping Wang +3
In coded aperture snapshot spectral imaging (CASSI), the captured measurement entangles spatial and spectral information, posing a severely ill-posed inverse problem for hyperspect…
Unfolding Framework with Complex-Valued Deformable Attention for High-Quality Computer-Generated Hologram Generation
Haomiao Zhang, Zhangyuan Li, Yanling Piao +6
Computer-generated holography (CGH) has gained wide attention with deep learning-based algorithms. However, due to its nonlinear and ill-posed nature, challenges remain in achievin…
Learning Radiance Fields from a Single Snapshot Compressive Image
Yunhao Li, Xiang Liu, Xiaodong Wang +2
In this paper, we explore the potential of Snapshot Compressive Imaging (SCI) technique for recovering the underlying 3D scene structure from a single temporal compressed image. SC…