Pose Representation

Pose representation in computer vision and related fields focuses on developing effective ways to encode and utilize information about the posture or configuration of objects, primarily humans and objects in 3D space. Current research emphasizes multi-modal approaches, integrating images, text descriptions, and 3D pose data using transformer-based architectures and autoencoders to create richer, more robust representations. These advancements are improving performance in various applications, including human image editing, 3D pose estimation from limited data, and motion prediction, ultimately leading to more accurate and efficient computer vision systems.