2 Dimensional Pose

Two-dimensional (2D) pose estimation focuses on accurately locating the key joints of a human body within a single image, often serving as a crucial stepping stone for more complex 3D pose estimation. Current research heavily emphasizes improving the accuracy and efficiency of 3D pose reconstruction from 2D data, employing various architectures like transformers, graph convolutional networks, and normalizing flows to address inherent ambiguities and limitations of single-view 2D information. This field is significant because accurate 3D pose estimation is vital for applications ranging from human-computer interaction and animation to healthcare and robotics, with ongoing efforts to improve robustness to occlusions and generalization across diverse datasets.