Web: http://arxiv.org/abs/2201.05989

May 5, 2022, 1:12 a.m. | Thomas Müller, Alex Evans, Christoph Schied, Alexander Keller

cs.LG updates on arXiv.org arxiv.org

Neural graphics primitives, parameterized by fully connected neural networks,
can be costly to train and evaluate. We reduce this cost with a versatile new
input encoding that permits the use of a smaller network without sacrificing
quality, thus significantly reducing the number of floating point and memory
access operations: a small neural network is augmented by a multiresolution
hash table of trainable feature vectors whose values are optimized through
stochastic gradient descent. The multiresolution structure allows the network
to disambiguate …

arxiv cv graphics neural

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