AI Learns Noise Filtering For Photorealistic Videos | Two Minute Papers #215
Two Minute Papers2 HN recommenders · recommended in 2 months, 2018-2019
65K views · 8 years ago · explainer · dated
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.
Cited as an accessible explanation of AI denoising, which underpins real-time ray tracing on RTX hardware.
8:34Enhancing Photorealism Enhancement
ISL and Collaborators
6.3M views • 5 years ago
5:26Neural Network Learns The Physics of Fluids and Smoke | Two Minute Papers #118
Two Minute Papers
209K views • 9 years ago
7:47This AI actually WORKS!!! - NVIDIA RTX Voice
ShortCircuit
1.8M views • 6 years ago
6:18A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras FI
1.3M views • 7 years ago
3:31CVPR 2018: Learning to See in the Dark
Chen Chen
190K views • 8 years ago
57:57Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition
Stanford University School of Engineering
2.9M views • 9 years ago
1:46NVIDIA RTX Real-Time Ray Tracing Tech Demo From Remedy Entertainment
NVIDIA GeForce
497K views • 8 years ago
5:10Dual Photography
mm648230
24K views • 17 years ago
37:20But how do AI images and videos actually work? | Guest video by Welch Labs
3Blue1Brown
2.2M views • 1 year ago
3:21ProFORMA: Probabilistic Feature-based On-line Rapid Model Acquisition
QiPanComputerVision
571K views • 17 years ago
17:403D Gaussian Splatting! - Computerphile
Computerphile
273K views • 2 years ago
20:39AI Language Models & Transformers - Computerphile
Computerphile
354K views • 7 years ago
5:58MarI/O - Machine Learning for Video Games
SethBling
11.5M views • 11 years ago
4:45Sparse Voxel Octree (SVO) Demo by Jon Olick
Zelexi
191K views • 17 years ago
17:08Playing a Neural Network's version of GTA V: GAN Theft Auto
sentdex
766K views • 5 years ago
6:36Face2Face: Real-time Face Capture and Reenactment of RGB Videos (CVPR 2016 Oral)
Matthias Niessner
5M views • 10 years ago
2:13Brigade 3.0 preview - Real-time path tracing
icelaglace
439K views • 12 years ago
1:19:08CS231n Winter 2016: Lecture1: Introduction and Historical Context
Andrej Karpathy
462K views • 10 years ago
4:28Eulerian Video Magnification
Miki Rubinstein
788K views • 14 years ago
5:513-Sweep: Extracting Editable Objects from a Single Photo, SIGGRAPH ASIA 2013
Daniel CohenOr
2.3M views • 13 years ago
5 comments from Hacker News
It's only briefly mentioned, but NVIDIA's recurrent denoising autoencoder is pretty amazing. link Two Minute Papers did a nice explanation of it: ▶ this video
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. ▶ this video
This uses a neural network ▶ this video video results start around 1:15 This one does not use a neural network: link
I don't think your estimations take into account the massive gains from AI denoising techniques such as ▶ this video
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] ▶ this video