We present Representation Autoencoders (RAE), a class of autoencoders that utilize pretrained, frozen representation encoders such as DINOv2 and SigLIP2 as encoders with trained ViT decoders. RAE can ...
Abstract: In recent years, supervised skeleton-based action recognition has achieved notable results. However, these methods rely on labeled data, which is both resource-intensive and time-demanding ...
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