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Found 5 papers, 3 papers with code
Cross-Domain 3D Hand Pose Estimation With Dual Modalities
To solve this problem, we present a framework for cross-domain semi-supervised hand pose estimation and target the challenging scenario of learning models from labelled multi-modal synthetic data and unlabelled real-world data.
Analyzing and Diagnosing Pose Estimation With Attributions
We present Pose Integrated Gradient (PoseIG), the first interpretability technique designed for pose estimation.
Generalized Domain Conditioned Adaptation Network
Domain Adaptation (DA) attempts to transfer knowledge learned in the labeled source domain to the unlabeled but related target domain without requiring large amounts of target supervision.
Domain Conditioned Adaptation Network
Most existing deep DA models only focus on aligning feature representations of task-specific layers across domains while integrating a totally shared convolutional architecture for source and target.
Deep Residual Correction Network for Partial Domain Adaptation
Deep domain adaptation methods have achieved appealing performance by learning transferable representations from a well-labeled source domain to a different but related unlabeled target domain.
