Search Results for author:
Found 8 papers, 5 papers with code
A Compact Implicit Neural Representation for Efficient Storage of Massive 4D Functional Magnetic Resonance Imaging
Functional Magnetic Resonance Imaging (fMRI) data is a widely used kind of four-dimensional biomedical data, which requires effective compression.
Lightweight High-Speed Photography Built on Coded Exposure and Implicit Neural Representation of Videos
In this work, by leveraging classical coded exposure imaging technique and emerging implicit neural representation for videos, we tactfully embed the motion direction cues into the blurry image during the imaging process and develop a novel self-recursive neural network to sequentially retrieve the latent video sequence from the blurry image utilizing the embedded motion direction cues.
SHoP: A Deep Learning Framework for Solving High-order Partial Differential Equations
Solving partial differential equations (PDEs) has been a fundamental problem in computational science and of wide applications for both scientific and engineering research.
CUTS: Neural Causal Discovery from Irregular Time-Series Data
Causal discovery from time-series data has been a central task in machine learning.
DarkVision: A Benchmark for Low-light Image/Video Perception
In this paper, we contribute the first multi-illuminance, multi-camera, and low-light dataset, named DarkVision, serving for both image enhancement and object detection.
TINC: Tree-structured Implicit Neural Compression
In this paper, we propose a Tree-structured Implicit Neural Compression (TINC) to conduct compact representation for local regions and extract the shared features of these local representations in a hierarchical manner.
SCI: A Spectrum Concentrated Implicit Neural Compression for Biomedical Data
To address this issue, we firstly derive a mathematical explanation for INR's spectrum concentration property and an analytical insight on the design of INR based compressor.
A Dual Sensor Computational Camera for High Quality Dark Videography
In this paper, we propose to build a dual-sensor camera to additionally collect the photons in NIR wavelength, and make use of the correlation between RGB and near-infrared (NIR) spectrum to perform high-quality reconstruction from noisy dark video pairs.
