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Found 4 papers, 1 papers with code
GaNI: Global and Near Field Illumination Aware Neural Inverse Rendering
In this paper, we present GaNI, a Global and Near-field Illumination-aware neural inverse rendering technique that can reconstruct geometry, albedo, and roughness parameters from images of a scene captured with co-located light and camera.
Inverse Global Illumination using a Neural Radiometric Prior
We train our radiance network and optimize scene parameters simultaneously using a loss consisting of both a photometric term between renderings and the multi-view input images, and our radiometric prior (the residual term).
Differentiable Neural Radiosity
We introduce Differentiable Neural Radiosity, a novel method of representing the solution of the differential rendering equation using a neural network.
Neural Radiosity
We introduce Neural Radiosity, an algorithm to solve the rendering equation by minimizing the norm of its residual similar as in traditional radiosity techniques.
