arXiv:2302.00592
Comparative Study of Parameter Selection for Enhanced Edge Inference for a Multi-Output Regression model for Head Pose Estimation
원문 초록
Magnitude-based pruning is a technique used to optimise deep learning models for edge inference. We have achieved over 75% model size reduction with a higher accuracy than the original multi-output regression model for head-pose estimation.
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From Neck to Head: Bio-Impedance Sensing for Head Pose Estimation
Event-based Egocentric Human Pose Estimation in Dynamic Environment
Continuous Normalizing Flows for Uncertainty-Aware Human Pose Estimation
Head Pose Estimation Based on 5D Rotation Representation
Domain Adaptation for Head Pose Estimation Using Relative Pose Consistency
SHPR-Net: Deep Semantic Hand Pose Regression From Point Clouds
토론
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