Skeleton Annotation

Skeleton annotation focuses on accurately representing human or object skeletal structures in digital form, primarily for applications in computer vision and medical imaging. Current research emphasizes developing robust and efficient methods for creating these annotations, including leveraging techniques like multi-teacher distillation, contrastive learning, and generative adversarial networks (GANs) to improve accuracy and reduce annotation effort. These advancements are crucial for improving the performance of downstream tasks such as action recognition, gait analysis, and medical image segmentation, ultimately leading to more accurate and efficient applications in various fields. The development of more efficient and accurate annotation methods is driving progress in areas like human-computer interaction and medical diagnosis.