How to Track Objects in Videos with Self-supervised Techniques | AISC

How to Track Objects in Videos with Self-supervised Techniques | AISC

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Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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Published on ● Video Link: https://www.youtube.com/watch?v=O8O__guO80E


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Guide
Duration: 38:17
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For slides and more information on the paper, visit https://ai.science/e/masta-memory-augmented-self-supervised-tracker--BJ9Chw0kECHfyEivCJS9

Speaker: Soufia Naseri; Discussion Facilitator: Fatemeh Darbehani; Host: Alireza Darbehani

Motivation:
Object tracking is gaining lots of attention and applications. MAST uses only 1 annotated data (pixel level) and achieves a high accuracy.

Comapring with unseen object categories MAST outperforms almost all of trained model using heavy supervision.

Self-supervised algorithms can serve as a strong competitor to their supervised counterparts due to demand for less computation power and better generalizability.



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