Meta Unveils CoTracker3 to Improve Tracking Using Pseudo Labelling Real Videos

Meta, on October 16, announced the launch of CoTracker3, a point tracker model to track videos, an upgrade to its CoTracker series of models featuring advanced AI technology. CoTracker3 is designed to handle situations where tracked points move out of view or temporarily occluded to overcome challenges in tracking objects across complex scenarios. 

Click here to check out the GitHub repository.

By introducing a semi-supervised learning method called ‘pseudo labelling’ on real videos, it allows the model to self-label parts of the data while Meta focuses on increasing the quality and quantity of training information without requiring fully annotated datasets.

According to the researchers, CoTracker3 can surpass trackers trained on ×1,000 more videos through its simple semi-supervised training protocol. By tracking points jointly, CoTracker3 handles occlusions …