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Found 4 papers, 1 papers with code
Compact Neural Graphics Primitives with Learned Hash Probing
Neural graphics primitives are faster and achieve higher quality when their neural networks are augmented by spatial data structures that hold trainable features arranged in a grid.
Learning Radio Environments by Differentiable Ray Tracing
Ray tracing (RT) is instrumental in 6G research in order to generate spatially-consistent and environment-specific channel impulse responses (CIRs).
Adaptive Shells for Efficient Neural Radiance Field Rendering
We then extract an explicit mesh of a narrow band around the surface, with width determined by the kernel size, and fine-tune the radiance field within this band.
Sionna RT: Differentiable Ray Tracing for Radio Propagation Modeling
Sionna is a GPU-accelerated open-source library for link-level simulations based on TensorFlow.
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