Summarize by Aili
A.I. Made These Movies Sharper. Critics Say It Ruined Them.
๐ Abstract
The article discusses the use of machine learning technologies in film restoration for new home video releases, and the controversy surrounding the results.
๐ Q&A
[01] Film Restoration Using Machine Learning
1. What are the key points about the use of machine learning in film restoration?
- Machine learning technologies are being used to restore classic films for new home video releases, allowing filmmakers to fine-tune and improve the image quality.
- The process involves removing small imperfections like scratches, dirt, and water stains from the original film negatives using a computer "copy-paste" tool.
- This restoration process was first used on the home video release of the film "Titanic" in 1998, which divided opinions - some praised the pristine quality, while others felt it removed the natural imperfections of the original film.
- As home video formats have improved over the decades, from VHS to Blu-ray and 4K, the restoration tools have also evolved, allowing for even more detailed refinement of the images.
- Recent 4K Blu-ray releases of James Cameron's films like "The Abyss," "True Lies," and "Aliens" have also used machine learning-powered restoration, which has again sparked controversy among viewers.
2. What are the key criticisms of the machine learning-based film restoration?
- Many viewers feel the restored versions look too pristine and unnatural, with a "glossy" or "lacquered" appearance that detracts from the original film experience.
- Some argue that the removal of natural imperfections and flaws in the original film negatives is a form of "ruining" the films, as it removes the authentic, gritty look that was intended by the filmmakers.
- There is a sentiment among some viewers that if the original negative had scratches or other flaws, those should be preserved rather than digitally erased.
[02] Controversy Around Restored Films
1. What are the key points about the controversy surrounding the machine learning-restored films?
- The use of proprietary machine learning software from companies like Park Road Post Production (owned by Peter Jackson) to clean up and refine the images in James Cameron's classic films has been a major source of controversy.
- Many viewers feel the resulting images, while technically more detailed and sharper, look "strange" and "unnatural" compared to the original theatrical or home video releases.
- There is a sense that the machine learning-powered restoration has gone too far in smoothing out the natural imperfections and textures of the original film, resulting in a "buffed" or "lacquered" appearance that detracts from the intended aesthetic.
- The level of detail and clarity achieved through the restoration process is described as "eye-popping," with water looking "crystalline" and colors being "bright and vivid." However, this hyper-realistic look is seen by many as a departure from the original artistic vision.
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