Just imagine the amount of time, money, and resources it takes to shoot and edit a video, and more so ever for businesses! You cannot afford to invest in videos for everything from promotional materials to even corporate training. But in this intense competition melee, you stand to lose if you cannot bring out engaging visual content to your customers. What then is the solution? Enter Artificial Intelligence or the deepfake videos.
Synthetic images and videos created using deepfake technology have the ability of a level playing field, especially, for small businesses and startups with a low marketing budget. They can generate quality videos and content similar to their bigger counterparts and reach their customers faster, consistently, and in a cost-effective way.
What is Deepfake AI?
Deepfake is a deep learning algorithm used in videos, images, and other digital content to make a fake appear real. Simply put, it is the AI that deceives.
When deepfake was just being invented, it used the generative adversarial network or the GAN technology. The technology uses two algorithms: a generator and a discriminator. The generator creates fake content. The role of the discriminator is to find out if the content is real or fake and pass on the information to the generator. The generator uses the analysis result to improve the next deepfake. They train themselves to recognize the real characteristics and patterns to synthesize fake images.
Deepfake technology nowadays uses machine learning to create fake videos. The self-supervised neural networks, also called autoencoders, are trained on many hours of real footage of the person to study the patterns, lighting effect, and other parameters. The trained network is now combined with computer graphics to superimpose the face of a one-person onto another. The AI program is trained to replace or synthesize faces, speech, and emotions.
Deepfake was first used for entertainment purposes. But of late, it is used by businesses to create AI synthetic videos and images for marketing and promotion.
Deepfake, when properly utilized, has a lot of benefits. But the irony is that it is used for all the wrong purposes on the internet.
How does Deepfake help in video analysis and synthesis?
Artificial intelligence can be applied to a multitude of video editing processes such as analysis and synthesis. In analysis, AI is used to extract useful information from digital video. Motion detection, object tracking, and action recognition are all examples of video analysis using AI.
Motion detection
This technology is used to identify movement within a masked region of the video over a period of time. It is useful in detecting human movement within a workspace and in monitoring wildlife on a natural reserve.
Object tracking
It involves tracking the movement of an object over time. It can be sued in avoiding pedestrians in a self-driving car, tracking people in a surveillance video, or following the faces of participants during a video call.
Action recognition
It is useful when you want to detect what’s happening in a video or to understand the human activities occurring on a webcam.
Now, let’s talk about the uses of AI or deepfake in video interpolation, video transfer, and video prediction that basically are video synthesis processes.
Video interpolation
This technique is used to predict the missing video frames from the previous and subsequent frames. It is used in a wide variety of video editing tasks such as creating slow-motion videos, restoring old film strips, and smoothing out security footage videos.
Video prediction
It is used to synthesize future video frames based on the previous ones. It requires a few frames of video as input to predict the next few frames as video output. This technology is still in its nascent stage and there aren’t many practical applications for it yet.
Video transfer
Video transfer or video-to-video synthesis is in which a new video is synthesized from simplified video input. A semantically segmented video is sued to produce a completely new video from scratch.
Video completion
This uses AI tools to complete the motion video, similar to image completion.
Video face synthesis
A quite popular technology now, it allows you to create synthetic videos of people speaking.
Video pose transfer
An advanced AI video synthesis technology, it creates videos of people’s movements
Video lip-syncing
Here, the lip movements are applied to the human face on a video track from an audio or text input.
Synthetic video generation platforms use deepfake technology to create artificial videos with realistic human avatars speaking words that are inputted through a text or audio format. The videos look almost natural in a conversational tone.
What are the benefits of using AI in video editing?
Artificial intelligence in video synthesis offers intelligent solutions to make video tasks simpler and easier. AI video synthesis lowers the video content creation costs and is fast and reliable.
You don’t need to be a pro in video editing. Artificial intelligence will do the work for you.AI will help in video editing techniques such as the application of filters and transitions, and figuring out the best angles, shots, and edits.You’ll be able to produce high-quality efficient videos within a short timeIt also does color correction and scene recognition making the visual experience richer.Bulk video editing becomes smarter with AI. Repetitive tasks can be fed to AI algorithms to get things done fast.
Conclusion
Deepfake video synthesis has already gone mainstream and businesses are using such videos for corporate onboarding, real estate and property listings, news articles, medical, education, and tutorials, and in sales and marketing.
DeepWord is a synthetic video generation platform to create artificial videos for your business at scale. You can create personalized videos, celebrity videos, educational tutorials, and much more in many languages using available avatars or by uploading your video. Discover the joys of video creation for your business with DeepWord, the possibilities are exciting and endless.
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