arXiv subjects

Shuchen Sun

Publications and source records attributed to Shuchen Sun.

7 recordsLinked to original sources

arXiv2026

Fast Implicit Neural Light Field Representation via Geometric Decomposition and Multi-Resolution Low-Rank Features

Implicit neural representations provide a compact and continuous way to reconstruct dense light fields from sampled ray coordinates. However, fast light field reconstruction remains challenging because a light field is a high-dimensional signal with strong spatial-angular redundancy and structured disparity variations. Directly fitting 4D ray coordinates with a neural network often requires considerable optimization time to recover both view appearance and cross-view consistency. To address this issue, this paper proposes a fast implicit light field representation based on geometric decomposition and multi-resolution low-rank features. The proposed method decomposes a 4D light field into a horizontal disparity plane, a spatial texture plane, and a vertical disparity plane. Each plane is represented by a low-rank structure that combines a low-resolution 2D grid with the element-wise product of two high-resolution 1D line features at multiple resolution levels. The fused features are decoded by a lightweight multilayer perceptron to predict RGB values. Experiments on public light field datasets show that the proposed method achieves competitive reconstruction quality while providing a better trade-off among model parameters, training time, and inference efficiency.

cs.CV↗

arXiv2026

Frequency-Decomposed INR for NIR-Assisted Low-Light RGB Image Denoising

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 light image restoration method based on Frequency Decoupled Implicit Neural Representation (FDINR). Based on the statistical prior of RGB-NIR cross-modal frequency correlations, specifically that low-frequency RGB signals are more reliable, whereas high frequency NIR signals exhibit higher correlation, we explicitly decompose images into distinct frequency components via multi-scale wavelet transforms and construct a dual-branch implicit neural representation framework. Within this framework, we design a cross modal differentiated frequency supervision mechanism, leveraging low light RGB to guide the reconstruction of low frequency luminance and color, and utilizing high-SNR NIR signals to constrain the generation of high frequency texture details, thereby achieving complementary advantages in the frequency domain. Furthermore, an uncertainty-based adaptive weighting loss function is introduced to automatically balance the contributions of different frequency tasks, solving the problems of color distortion and artifacts caused by rigid fusion in the spatial domain common in traditional methods. Experimental results demonstrate that FD-INR not only effectively restores image luminance consistency and structural details but also, benefitting from its implicit continuous representation, outperforms existing methods in arbitrary-resolution reconstruction tasks, significantly enhancing the reliability of low light perception.

cs.CV↗

arXiv2025

Infrared and Visible Image Fusion Based on Implicit Neural Representations

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 requirements. This paper proposes an image fusion method based on Implicit Neural Representations (INR), referred to as INRFuse. This method parameterizes a continuous function through a neural network to implicitly represent the multimodal information of the image, breaking through the traditional reliance on discrete pixels or explicit features. The normalized spatial coordinates of the infrared and visible light images serve as inputs, and multi-layer perceptrons is utilized to adaptively fuse the features of both modalities, resulting in the output of the fused image. By designing multiple loss functions, the method jointly optimizes the similarity between the fused image and the original images, effectively preserving the thermal radiation information of the infrared image while maintaining the texture details of the visible light image. Furthermore, the resolution-independent characteristic of INR allows for the direct fusion of images with varying resolutions and achieves super-resolution reconstruction through high-density coordinate queries. Experimental results indicate that INRFuse outperforms existing methods in both subjective visual quality and objective evaluation metrics, producing fused images with clear structures, natural details, and rich information without the necessity for a training dataset.

cs.CV↗

arXiv2024

Deformability, inherent mechanical properties and chemical bonding of Al11Nd3 in Al-Nd target material

Microstructure uniformity of the Al-Nd target materials with Al11Nd3 significantly affects the performance of the fabricated film, which is widely used as wiring material in largesize thin-film transistor liquid crystal display (TFT-LCD) panels. Understanding the inherent mechanical properties and chemical bonds of Al11Nd3 is crucial for homogenizing the Al-Nd target. Here, by a combined experimental and ab-initio theoretical study, the microstructure and deformability of the Al-3wt%Nd alloy and the inherent mechanical properties and chemical bonds of Al11Nd3 are investigated comprehensively. The Al-3wt%Nd alloy is composed of the pre-eutectic {\alpha}-Al matrix and the eutectic {\alpha}-Al and a high stable {\alpha}-Al11Nd3 phases. During the plastic deformation, the eutectic microstructure transforms from a cellular to a lamellar shape, while the morphology and dimension of {\alpha}-Al11Nd3 are not changed significantly. By examining ideal tensile strength, elastic moduli, hardness and brittleness-ductility, the hardnessbrittleness of {\alpha}-Al11Nd3 is quantitatively evaluated, accounting for its difficulties of plastic deformation and fragmentation. Combining band structure, population analysis, topological analysis and crystal orbital Hamilton population, it is revealed that {\alpha}-Al11Nd3 possesses two types of chemical bonds: the Nd-Al and Al-Al bonds. The former is a typical ionic bond with electron transfer from Nd to Al, while the latter, dominated by both 3s-3p and 3p-3p interactions, is a weak covalent bond. The mixed chemical bond is responsible for the high hardness-brittleness of {\alpha}-Al11Nd3. This work is expected to lay a foundation for Al-Nd alloy and catalyze the fabrication of high-quality Al-Nd target materials.

cond-mat.mtrl-sci↗

arXiv2023

Finite-temperature ductility-brittleness and electronic structures of Al$_{n}$Sc (n=1, 2 and 3)

Finite-temperature ductility-brittleness and electronic structures of Al$_3$Sc, Al$_2$Sc and AlSc are studied comparatively by first-principles calculations and ab-initio molecular dynamics. Results show that Al$_3$Sc and Al$_2$Sc are inherently brittle at both ground state and finite temperatures. By contrast, AlSc possesses a significantly superior ductility evaluated from all Pugh's, Pettifor's and Poisson's ductility-brittleness criteria. At ground state, AlSc meets the criteria of ductile according to Pugh's and Poisson's theories, while it is categorized as the brittle in the frame of Pettifor's picture. With the increasing temperature, the ductility of all the studied compounds exhibits a noticeable improvement. In particular, as the temperature rises, the Cauchy pressure of AlSc undergoes a transition from negative to positive. Thus, at high temperatures (T > 600 K), AlSc is unequivocally classified as the ductile from all criteria considered. In all Al$_3$Sc, Al$_2$Sc and AlSc, the Al-Al bond, originated from s-p and p-p orbital hybridizations, and the Al-Sc bond, dominated by p-d covalent hybridization, are the first and second strongest chemical bonds, respectively. To explain the difference in mechanical properties of the studied compounds, the mean bond strength (MBS) is evaluated. The weaker Al-Al bond in AlSc, leading to a smaller MBS, could be the origin for the softer elastic stiffness and superior intrinsic ductility. The longer length of the Al-Al bond in AlSc is responsible for its weaker bond strength. Furthermore, the enhanced metallicity of the Al-Al bond in AlSc would also contribute to its exceptional ductility.

cond-mat.mtrl-sci↗

arXiv2014

Development of a Quasi-Periodic Undulator for the HLS

China's first quasi-periodic undulator (QPU) has been developed for the Hefei Light Source (HLS). It uses a magnetic configuration with varied thicknesses of NdFeB blocks, based on the QPU of European Synchrotron Radiation Facility (ESRF). Depression of 3rd harmonic radiation is significantly improved over the ESRF QPU, as deduced from the measured magnetic fields. A method of configuring shims of different geometries and sizes, based on a symmetric principle to correct multi-pole field integrals, was demonstrated.

physics.acc-ph↗

arXiv2013

Development of A Modified Quasi-periodic Undulator for HLS

A modified quasi periodic undulator (QPU) is developed and to be installed at Hefei Light Source (HLS).Magnet dimensions optimization is applied. High harmonics contamination is eliminated from the fundamental emission effectively according to the field tests. The depression ratio of 3rd harmonic is increased by an order of magnitude than the current device with other harmonics well reduced simultaneously. The significance of the modification measure is verified practically. The design, measurement and commissioning of the device is described.

physics.acc-ph↗