YouTube Introduces Machine Learning Individual Object Recognition on Videos and Facebook Follows Next

Artificial Intelligence is one of the greatest achievements in the tech world and while machine learning was only limited to reading still frames up until now and is quite efficient in it, the next step being taken in the advancement of machine learning and artificial intelligence is identifying individual objects within video in order to open up new considerations in brand placement, visual effects, accessibility features and more.

The first and successful step taken towards making AI identify individual objects within video was done by Google. Google had been working towards accomplishing this feature for some time now and after a lot of efforts it has now introduced new advances in its YouTube option which includes being able to tag products in that are present in video clips and provide direct links to shop for those products.

This simply means that companies now can tag their products in YouTube videos no matter at what timing it is being displayed, it can tag its product at that specific time. Along with this it will also provide direct shopping options, facilitating broader ecommerce opportunities in the app.

After the successful introduction of this feature in YouTube, Facebook is taking the next step and introducing a similar feature on its platform and the company claims that their feature will be much better at singling out individual objects within video frames.

Facebook explained that they have collaborated with researchers at Inria with whom they have developed a new method called DINO. This method will be used to train Vision Transformers (ViT) with no supervision. The company has claimed that besides setting a new state of the art among self-supervised methods, this approach leads to a remarkable result that is unique to this combination of AI techniques. Facebook further said that their model can discover and segment objects in an image or a video with absolutely no supervision and without being given a segmentation-targeted objective and all this will make this process effectively automated.

Hence that is why the company claims that their feature is the best of the best.

The company further said that segmenting objects is one of the hardest challenges in computer vision because it requires that AI truly understand what is in an image. It helps facilitate tasks ranging from swapping out the background of a video chat to teaching robots that navigate through a cluttered environment however all this done with supervised learning and requires large volumes of annotated examples. But Facebook’s new technology DINO will show high accurate segmentation with only self-supervised learning and a suitable architecture making it a lot easier and uncomplicated.

This new option will then help Facebook display and tag products similar to YouTube in the videos on their application along with other features related to AR and visual tools that could lead to much more advanced, more immersive Facebook functions which will definitely help the company in incorporating further data and personalization.

Facebook is still working towards this feature and once it is launched we cannot wait to see if it out does YouTube’s similar feature or not. However, we know that both YouTube and Facebook have always delivered their best and therefore we are sure that they will deliver the best this time as well.

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