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Found 3 papers, 2 papers with code
Skeleton-Based Human Action Recognition with Noisy Labels
In this study, we bridge this gap by implementing a framework that augments well-established skeleton-based human action recognition methods with label-denoising strategies from various research areas to serve as the initial benchmark.
Exploring Few-Shot Adaptation for Activity Recognition on Diverse Domains
In this work, we focus on Few-Shot Domain Adaptation for Activity Recognition (FSDA-AR), which leverages a very small amount of labeled target videos to achieve effective adaptation.
Smoothed Gaussian Mixture Models for Video Classification and Recommendation
SGMM represents each video by the parameters of a Gaussian mixture model (GMM) trained for that video.
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