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This review aims to explore the evolution of pose estimation methods and architectures, highlighting key advancements.

June 6, 2026ComputersOpen Access

Deep Human Pose Estimation: A Conceptual Review of Paradigms, Progress, and Frontiers

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This review aims to explore the evolution of pose estimation methods and architectures, highlighting key advancements.
Analyzed recent advances in pose estimation across five structural pillars: Representation, Architecture, Ambiguity and Generalization, Context Extension, and Applications.
Focused on the transition from traditional classifications to a more conceptual framework for understanding progress in the field.
Identified key advancements in representations, such as the shift from pixel regression to heatmaps and probabilistic models.
Discussed the evolution of architectures from multi-stage CNNs to modern transformer models.
Highlighted the importance of tackling uncertainty and occlusion through self-supervised learning and other novel approaches.

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Conceptual review examines evolution of pose estimation methods and applications, indicating future research paths.

Diallo et al. (2026) studied this question.

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