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Found 11 papers, 7 papers with code
Compressed 3D Gaussian Splatting for Accelerated Novel View Synthesis
Recently, high-fidelity scene reconstruction with an optimized 3D Gaussian splat representation has been introduced for novel view synthesis from sparse image sets.
Postprocessing of Ensemble Weather Forecasts Using Permutation-invariant Neural Networks
Statistical postprocessing is used to translate ensembles of raw numerical weather forecasts into reliable probabilistic forecast distributions.
Neural Fields for Interactive Visualization of Statistical Dependencies in 3D Simulation Ensembles
We present the first neural network that has learned to compactly represent and can efficiently reconstruct the statistical dependencies between the values of physical variables at different spatial locations in large 3D simulation ensembles.
Fast Neural Representations for Direct Volume Rendering
Despite the potential of neural scene representations to effectively compress 3D scalar fields at high reconstruction quality, the computational complexity of the training and data reconstruction step using scene representation networks limits their use in practical applications.
Analytic Ray Splitting for Controlled Precision DVR
For direct volume rendering of post-classified data, we propose an algorithm that analytically splits a ray through a cubical cell at the control points of a piecewise-polynomial transfer function.
Comparison of classical and Bayesian imaging in radio interferometry
CLEAN, the commonly employed imaging algorithm in radio interferometry, suffers from a number of shortcomings: in its basic version it does not have the concept of diffuse flux, and the common practice of convolving the CLEAN components with the CLEAN beam erases the potential for super-resolution; it does not output uncertainty information; it produces images with unphysical negative flux regions; and its results are highly dependent on the so-called weighting scheme as well as on any human choice of CLEAN masks to guiding the imaging.
Instrumentation and Methods for Astrophysics Applications
Visual Analysis of Multi-Parameter Distributions across Ensembles
For an ensemble of data points in a multi-parameter space, we present a visual analytics technique to select a representative distribution of parameter values, and analyse how representative this distribution is in all ensemble members.
Human-Computer Interaction Graphics
Inverting the Feature Visualization Process for Feedforward Neural Networks
By means of Inverse Feature Visualization, we intend to provide an alternative view on a networks sensitivity to certain inputs that considers feature objectives rather than activations.
Learning Adaptive Sampling and Reconstruction for Volume Visualization
A central challenge in data visualization is to understand which data samples are required to generate an image of a data set in which the relevant information is encoded.
Sparse Surface Constraints for Combining Physics-based Elasticity Simulation and Correspondence-Free Object Reconstruction
In a number of tests using synthetic datasets and real-world measurements, we analyse the robustness of our approach and the convergence behavior of the numerical optimization scheme.
Graphics I.6
Volumetric Isosurface Rendering with Deep Learning-Based Super-Resolution
With the advent of deep learning networks, a number of architectures have been proposed recently to infer missing samples in multi-dimensional fields, for applications such as image super-resolution and scan completion.
