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Found 2 papers, 2 papers with code
Semi-supervised Body Parsing and Pose Estimation for Enhancing Infant General Movement Assessment
We collected a new clinical IMV dataset with GMA annotations, and our experiments show that SPN models for body parsing and pose estimation trained on the first two datasets generalize well to the new clinical dataset and their results can significantly boost the CRNN-based GMA prediction performance.
AggPose: Deep Aggregation Vision Transformer for Infant Pose Estimation
We show that AggPose outperforms hybrid model HRFormer and TokenPose in the infant pose estimation dataset.
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