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AI Learns Noise Filtering For Photorealistic Videos | Two Minute Papers #215

Two Minute Papers · 64.6K views · 2017-12-17 · 4:17

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Overview

A Two Minute Papers episode on NVIDIA's recurrent denoising autoencoder, which cleans up noisy Monte Carlo path-traced image sequences. It shows how a neural network can produce usable renders from very few samples.

On Hacker News

Cited as an accessible explanation of AI denoising, which underpins real-time ray tracing on RTX hardware.

Recommended by 2 HN people across 2 months · HN mentions 2018–2019

Topics

Computer graphics & renderingMachine learning & deep learning
Search by tags
denoisingpath tracingautoencodernvidiareal-time rendering

What people said

jonas21 · 2019-09 · Recommendation

It's only briefly mentioned, but NVIDIA's recurrent denoising autoencoder is pretty amazing. [LINK] Two Minute Papers did a nice explanation of it: [VIDEO]

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halflings · 2018-06 · Recommendation

Disney actually does a lot of research combining the world of graphics with deep learning. Some examples that you might appreciate (from the excellent channel "Two Minute Papers"): . "Disney's AI Learns To Render Clouds" [0] . "AI Learns Noise Filtering For Photorealistic Videos" [1] [0] [LINK] [1] [VIDEO]

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kuzehanka · 2019-03 · Reference

Deep learning denoiser. I don't know if NVIDIA came up with some marketing term for it. It's what allows RTX to produce meaningful images at all despite the renderer running at 0.5-2 samples per pixel which looks little better than random noise. I kind of assumed they'd call it DLDN because they called their deep learning supersampling DLSS. I guess not, go figure. [VIDEO]

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Sources

Video by Two Minute Papers, played through YouTube.

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