AI RESEARCH
Learning Sparse BRDF Measurement Samples from Image
arXiv CS.CV
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ArXi:2604.26740v1 Announce Type: new Accurate BRDF acquisition is important for realistic rendering, but dense gonioreflectometer measurements are slow and expensive. We study how to select a small number of BRDF measurements that are most useful for reconstructing material appearance under a learned reflectance prior. Our method combines a set encoder for sparse coordinate-value observations, a pretrained hypernetwork-based BRDF reconstructor, and a differentiable renderer. During sampler.