Abstract
The metaverse is gradually expanding. There is a growing number of photo and video recordings of metaverse virtual worlds being used in multiple domains, and the collection of these recordings is a rapidly growing field. An essential element of the metaverse and its recordings is the concept of avatars. In this paper, we present the novel task of avatar detection in metaverse recordings, supporting semantic retrieval in collections of metaverse recordings and other use cases. Our work addresses the characterizations and definitions of avatars and presents a new model that supports avatar detection. The latest object detection algorithms are trained and tested on a variety of avatar types in metaverse recordings. Our work achieves a significantly higher level of accuracy than existing models, which encourages further research in this field.
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