Hard and fast point sampling with NeRF
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Опубликовано 23 сентября 2024, 9:54
Neural radiance field (NeRF) training can create incredibly complex 3D scenes from 2D images – at a high computational cost. Our method uses hard sampling to efficiently optimize these networks at twice the speed, saving both time and memory otherwise lost through traditional random sampling. Imagine NeRF’s potential in efficiently representing a variety of multimedia content (beyond just scene representation) with Nokia-enabled consumer-grade hardware compatibility.
Like the sound of speeding up and reducing the memory cost of neural network training down to inference levels? Read the paper by Juuso Korhonen, Goutham Rangu, Hamed Rezazadegan Tavakoli and Juho Kannala to learn more: arxiv.org/abs/2408.03193
Like the sound of speeding up and reducing the memory cost of neural network training down to inference levels? Read the paper by Juuso Korhonen, Goutham Rangu, Hamed Rezazadegan Tavakoli and Juho Kannala to learn more: arxiv.org/abs/2408.03193
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