Neural Mesh Simplification is a novel approach to reduce the resolution of 3D meshes while preserving their appearance. Unlike traditional simplification methods that collapse edges in a greedy iterative manner,
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Our data pipeline is illustrated in Fig.2. Mesh data is offline optimized for size and rendering efficiency. The raw data is stored in the STL format and has a size ranging from 200 to 500 MB per sample. We applied offline mesh optimization (mainly vertex simplification) and generated three...
Linear Regression (LR) model requires Markovian simplification and follows the equation:(9)zˆt+1=Wzzˆt+Wuut+Wmm+b,where parameters φ={Wz,Wu,Wm,b} are obtained analytically. Fully-Connected Neural Network (FCNN) is another Markovian model able to approximate a much broader class of fu...
All the used k points are the occupied k points from Hartree–Fock calculation using Monkhorst-Pack mesh offset by kS in cc-pVDZ basis, and the mesh size is the same as the supercell. All the expectation values for distribution ∣ψ∣2 are evaluated via the Monte Carlo approach, and then...
computational platforms like CUDA[25], PINNs enable highly parallelisable computational processes. Secondly, PINNs can intrinsically ensure adherence to physical laws by incorporating the governing equations into the training process. Moreover, compared to traditional discrete numerical methods, the mesh-...
The geometry of the computational domain and the mesh are created using the open-source software GMSH [71]. The full-order FE solutions are computed using the package FEniCS [72,73], and the neural network training and prediction phase are implemented using the package PyTorch [74]. The ...
mkdir external cd external git clone https://github.com/nghorbani/human_body_prior.git cd human_body_prior python setup.py developData PreprocessRun "DFaust_generate.py" to preprocess data. Note that this may take a long time due to the mesh simplification (the open3d API mesh_o3d....
Train MESH2IR Codes are available insidetrainfolder. Download theGWA datasetfor 100 different meshes using the following command. Note that this is a subset of data that is used to train MESH2IR. You can get the full dataset using the followinglink. You need to get 3D-FRONT license before...
To cluster these offsets, we used the built-in MATLAB function kde.m (with 256 mesh points) to perform kernel density estimation of the distribution of offsets for each fly on each trial (note that for previous versions of the analyses, we used the version of kde.m created by Zdravko ...