Human Pose Estimation

Human pose estimation aims to accurately determine the location of human body joints from various input modalities, such as images, videos, or sensor data. Current research focuses on improving accuracy and efficiency, particularly in challenging scenarios like occlusions and low-resolution inputs, through the development and refinement of transformer-based models, graph convolutional networks, and other deep learning architectures. These advancements have significant implications for numerous applications, including human-robot interaction, healthcare, sports analysis, and augmented/virtual reality, by enabling more robust and efficient systems for movement analysis and human-computer interaction.