Search Results for author:
Found 5 papers, 3 papers with code
Stereo Event-based Particle Tracking Velocimetry for 3D Fluid Flow Reconstruction
Existing Particle Imaging Velocimetry techniques require the use of high-speed cameras to reconstruct time-resolved fluid flows.
Neural Adaptive SCEne Tracing
Neural rendering with implicit neural networks has recently emerged as an attractive proposition for scene reconstruction, achieving excellent quality albeit at high computational cost.
NeAT: Neural Adaptive Tomography
Through a combination of neural features with an adaptive explicit representation, we achieve reconstruction times far superior to existing neural inverse rendering methods.
Ranked #4 on
Low-Dose X-Ray Ct Reconstruction
on X3D
IntraTomo: Self-Supervised Learning-Based Tomography via Sinogram Synthesis and Prediction
After getting estimated through the sinogram prediction module, the density field is consistently refined in the second module using local and non-local geometrical priors.
Ranked #6 on
Novel View Synthesis
on X3D
Computed Tomography (CT)
Low-Dose X-Ray Ct Reconstruction
+3
Super-Resolution and Sparse View CT Reconstruction
As a second, smaller contribution, we also show that when using such a proximal reconstruction framework, it is beneficial to employ the Simultaneous Algebraic Reconstruction Technique (SART) instead of the commonly used Conjugate Gradient (CG) method in the solution of the data term proximal operator.
