CVPR 2018: Learning to See in the Dark
What it is
A short video accompanying the CVPR 2018 paper Learning to See in the Dark. It shows a neural network producing sharp images from very low-light raw sensor data, compared against denoising approaches.
Why Hacker News recommends it
HN commenters flag it as a remarkable machine-learning result, notably for showing that training on raw images beats JPEG.
- 1 people recommended it
- 1 different months
- 0 strong recommendations
- first 2018, last 2020
What HN commenters said
“Remarkable machine learning result for "producing astoundingly sharp photos in very low light”
Remarkable low-light image enhancement result.
isp, 2018-05 · Recommendation · in “Learning to See in the Dark”
Excerpts from Hacker News comments, linked to the originals. Summaries and labels were written by a language model from those comments.
Topics: computer vision, raw images, denoising, cvpr, neural networks
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