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Aligning Non-Causal Factors for Transformer-Based Source-Free Domain Adaptation
Conventional domain adaptation algorithms aim to achieve better generalization by aligning only the task-discriminative causal factors between a source and target domain.
Non-Local Latent Relation Distillation for Self-Adaptive 3D Human Pose Estimation
To this end, we cast 3D pose learning as a self-supervised adaptation problem that aims to transfer the task knowledge from a labeled source domain to a completely unpaired target.
Ranked #5 on
Unsupervised 3D Human Pose Estimation
on Human3.6M
Uncertainty-Aware Adaptation for Self-Supervised 3D Human Pose Estimation
The advances in monocular 3D human pose estimation are dominated by supervised techniques that require large-scale 2D/3D pose annotations.
Ranked #8 on
Unsupervised 3D Human Pose Estimation
on Human3.6M
Monocular 3D Human Pose Estimation
Unsupervised 3D Human Pose Estimation
+2
