Using neural networks has become commonplace in our lives. Their capabilities allow for video processing, enhancing its quality by applying artificial intelligence. This article discusses techniques and specific neural networks for working with video content.
Video Processing with Neural Networks
If a recording is old and taken with a poor camera, the image quality will be disappointing. Previously, picture quality restoration was done manually by people.
The drawbacks of this method were its cost and time-consuming nature. AI technology assists in working with video materials. It is already applied in medicine, education, and business.
For example, it’s possible to enhance a video from 480p to 1080p and even higher. There’s a chance to restore old cinematic masterpieces and show them to the younger generation.
The innovation has introduced film dubbing. For instance, Deepdub Go (a startup from Israel) automatically translates into 65 languages. Just like the neural network for video processing in Russian by Yandex. It’s by default integrated into the Yandex Browser. Simply enable the function before watching a movie/clip, and the translation will start.
In familiar editors, such as Photoshop and Premiere Pro, AI features have already appeared, allowing for a speedier workflow.
Neural Network for Anime Video Processing
These neural networks have gained popularity in Asian countries, often developed by students. For example, the AnimeGAN neural network turns everyday photos into anime drawings and even clips. The user only needs to upload their image or video material.
These applications offer a range of filters. For instance, Hayao in the style of Hayao Miyazaki, Shinkai in the style of Makoto Shinkai. The source code is publicly available, and enthusiasts continue to make their modifications.
The second in popularity is Kaiber AI, specialized in transforming people into anime heroes. With this artificial intelligence, a clip for Linkin Park was created. The user selects the image aesthetic.
Neural Network for Video to Animation Conversion
A prime example is Phenaki. It simulates human movements and animates characters. Already used by content managers to create advertising and video content.
Deepfake stirs controversy because it allows creating fake videos with the participation of real people. Actively used for political propaganda. For instance, tabloid media apply it to create slander.
Runway App - a neural network for converting video into animation, can be used to add effects to animation. It generates visual additions that can be attached to an existing animated clip.
How to Work With Them
In most neural networks, uploading a photo or video material is quite simple. However, some possess advanced functions. The most popular are Control Net and Stable Diffusion.
The former - a neural network for video processing, allows influencing production, for instance, changing shapes, colors, and other characteristics of the material. It helps set the right mood and convey the correct message. It’s already partially applied in film production.
Diffusion - a behemoth in the realm of video. Simply provide the first frame, and the artificial intelligence will continue it. This is achieved by generating random noise signals. Technically very complex, but straightforward for the average user. Frequently used in advertising.
List of Other Examples:
• Midjorney - creates pictures and videos on demand.
• Imagen Video - more for content management and analysis of target audience engagement.
• Lumen5 - a neural network for video processing based on text.
• Visper - a Russian service from Sber. A neural network for video processing in Russian creates clips with virtual characters.
• Synthesia - similar functions to the example above.
• Fliki - converts text to animated format.
• Pictory AI - unique feature: turns URL into video.
All applications have limitations in the free version, but it’s sufficient for creating basic animations. Platforms may not have restrictions but add their watermark to the finished work.
Pros and Cons
There are advantages and disadvantages to everything. Let’s look at them in more detail.
Pros:
• The possibility of restoring old video files.
• Video processing with neural networks speeds up content production.
• Reduces the cost of creating video content, as expensive equipment is not required.
• The possibility of creating personalized content. Increases engagement.
Cons:
• All these technologies can be used for various purposes, including negative ones, such as spreading fake news and blackmail.
• Ethical norms of many people can be violated due to the creation of unrealistic content with their participation.
It could be said that the drawbacks are far-fetched, but they exist. However, the advantages are plentiful. This is just the tip of the iceberg of what neural networks can do, and not all possibilities are yet discovered.
There are official plugins from Open AI as well as user-made additions. What facilitates work in creating advertising and producing video content. Processing video with neural networks becomes even easier!
