Pose Estimation Pipeline

Pose estimation pipelines aim to automatically determine the position and orientation of objects or humans in images or videos, a crucial task with applications ranging from robotics to clinical research. Current research focuses on improving accuracy and robustness across diverse scenarios, employing techniques like contrastive learning to integrate multiple data modalities (e.g., images, 2D/3D poses) and transformer networks to leverage geometric information for enhanced 6D pose estimation. These advancements are enabling more reliable and efficient pose estimation in challenging environments, such as underwater settings or with low-textured objects, and facilitating broader adoption in fields requiring precise movement analysis.