Hierarchical NeRF with JAX3D for Volumetric Rendering, Novel-View Synthesis, and 3D Reconstruction
MarkTechPost Sana Hassan
A tutorial built an end-to-end hierarchical NeRF in JAX using Flax, Optax, and jax3d’s volume-rendering primitives, including synthetic multi-view data generation and evaluation with PSNR and marching-cubes extraction. The configuration uses 24 training views at 64x64 resolution. The result is a trainable pipeline that performs novel-view synthesis and 3D reconstruction by combining coarse and fine networks with hierarchical importance sampling in volume rendering.
Why it matters
In this tutorial, we build an end-to-end hierarchical Neural Radiance Field (NeRF) using JAX, Flax, Optax, and the volume-rendering primitives provided by jax3d. We first construct a synthetic multi-view dataset from an analytic scene containing volumetric geometry and view-dependent radiance, using sample_along_rays and volume_rendering to establish the forward rendering process. We then implement a NeRF […] The post Hierarchical NeRF with JAX3D for Volumetric Rendering, Novel-View Synthesis, and 3D Reconstruction appeared first on MarkTechPost.
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