To extend WHAM to handle multiple people in a scene and their interactions, the network architecture could be modified to incorporate multi-person pose estimation techniques. This would involve detecting and tracking multiple individuals in the video frames, assigning unique identifiers to each person, and then estimating the 3D pose and motion of each individual separately. By implementing a mechanism to handle occlusions and interactions between people, WHAM could accurately reconstruct the 3D motion of multiple individuals in a scene. Additionally, incorporating social interaction cues and context-aware modeling could further enhance the understanding of how people interact with each other in a given environment.