Lifelong Domain Adaptation for 3D Human Pose Estimation
Research Paper#Computer Vision, Domain Adaptation, Human Pose Estimation🔬 Research|Analyzed: Jan 3, 2026 16:57•
Published: Dec 29, 2025 20:56
•1 min read
•ArXivAnalysis
This paper introduces a novel task, lifelong domain adaptive 3D human pose estimation, addressing the challenge of generalizing 3D pose estimation models to diverse, non-stationary target domains. It tackles the issues of domain shift and catastrophic forgetting in a lifelong learning setting, where the model adapts to new domains without access to previous data. The proposed GAN framework with a novel 3D pose generator is a key contribution.
Key Takeaways
- •Introduces a novel task: lifelong domain adaptive 3D human pose estimation.
- •Addresses domain shift and catastrophic forgetting in a lifelong learning setting.
- •Proposes a GAN framework with a novel 3D pose generator.
- •Demonstrates superior performance on diverse domain adaptive 3D HPE datasets.
Reference / Citation
View Original"The paper proposes a novel Generative Adversarial Network (GAN) framework, which incorporates 3D pose generators, a 2D pose discriminator, and a 3D pose estimator."