Multi Person 3D Pose

Multi-person 3D pose estimation aims to accurately determine the three-dimensional positions and shapes of multiple individuals within a scene, often from image or video data. Current research emphasizes improving accuracy and efficiency through novel architectures like transformers and graph neural networks, addressing challenges such as occlusion, varying viewpoints, and the need for robust person identification. These advancements are crucial for applications ranging from video surveillance and human-computer interaction to animation and virtual reality, enabling more natural and realistic representations of human movement and interaction in digital environments.