Taichi-based Differentiable SciVis Renderer for PyTorch
- Differentiable Rendering
- Differentiating on transfer functions (TFs)
- Backpropagation (BP) on transfer functions with a momentum optimizer
- Differentiating and BP on volume
- Advance loss for compensating high frequency signals
- Direct Volume Rendering
- Ray jittering
- Engineering
- Advance data layout for speedup
- Logging on TFs
- PyTorch integration