While deep learning is taking us into the future, it’s also opening windows into the past.
What’s new: Machine learning-savvy Redditor Denis Shiryaev brought 100-year-old silent film footage of New York City into the 21st century by automatically sharpening the picture, boosting the frame rate, and adding color.
How he did it: Shiryaev obtained eight minutes of footage shot by a Swedish film maker in 1911. He spent five days running the movie through a gauntlet of neural nets.
- Shiryaev used Enhanced Super-Resolution Generative Adversarial Networks to compute additional pixels, boosting resolution to 4K (approximately 4,000 pixels horizontally).
- He used Depth-Aware Video Frame Interpolation to generate in-between frames, raising the frame rate to 60 per second. Film shot in the early 1900s typically had much lower frame rates, making them look sped-up and jerky.
- He applied DeOldify to colorize the imagery. He noted on Reddit that he isn’t completely sold on that process, because the colors aren’t historically accurate.
- The sound effects were digital audio clips. Several commenters said they recognized horse whinnies from the video game Age of Empires II.
Behind the news: Shiryaev has used these procedures to update footage of Moscow in 1896, an iconic film from the same year that shows a French train pulling into station and Apollo 16 astronauts driving their moon buggy across the lunar surface in 1972.
Why it matters: Shiryaev’s work brings these pieces of the past to life, overcoming the poor image quality, jerky movements, and lack of colors that diminish so much historic film. Similar treatment no doubt would perk up careworn Hollywood classics as well.
We’re thinking: We can’t wait to up-res old home videos. It’s about time our parents’ 1980s hairstyles were revealed in high def.