5 citations · 5 across the 10 of their papers we have counts for
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Fast Implicit Neural Light Field Representation via Geometric Decomposition and Multi-Resolution Low-Rank Features
Yao Guo, Ligen Shi, Shuchen Sun +2
Implicit neural representations provide a compact and continuous way to reconstruct dense light fields from sampled ray coordinates. However, fast light field reconstruction remain…
Frequency-Decomposed INR for NIR-Assisted Low-Light RGB Image Denoising
Ligen Shi, Zengyu Pang, Chang Liu +2
Addressing the issues of severe noise and high frequency structural degradation in visible images under low-light conditions, this paper proposes a Near Infrared (NIR) aided low li…
Adaptive Local Frequency Filtering for Fourier-Encoded Implicit Neural Representations
Ligen Shi, Jun Qiu, Yuhang Zheng +2
Fourier-encoded implicit neural representations (INRs) have shown strong capability in modeling continuous signals from discrete samples. However, conventional Fourier feature mapp…
Physics-Inspired Gaussian Kolmogorov-Arnold Networks for X-ray Scatter Correction in Cone-Beam CT
Xu Jiang, Huiying Pan, Ligen Shi +3
Cone-beam CT (CBCT) employs a flat-panel detector to achieve three-dimensional imaging with high spatial resolution. However, CBCT is susceptible to scatter during data acquisition…
Infrared and Visible Image Fusion Based on Implicit Neural Representations
Shuchen Sun, Ligen Shi, Chang Liu +2
Infrared and visible light image fusion aims to combine the strengths of both modalities to generate images that are rich in information and fulfill visual or computational require…
Matching entropy based disparity estimation from light field
Ligen Shi, Chang Liu, Di He +2
A major challenge for matching-based depth estimation is to prevent mismatches in occlusion and smooth regions. An effective matching window satisfying three characteristics: textu…