Mesh Estimation

Mesh estimation, particularly of humans, aims to reconstruct 3D body shapes from various input modalities like images, 2D keypoints, or even WiFi signals. Current research focuses on improving accuracy and efficiency, often employing deep learning models such as graph neural networks and diffusion models, and addressing challenges like data scarcity, occlusion, and consistency across frames. These advancements have implications for diverse fields, including animation, virtual reality, robotics, and healthcare, by enabling more realistic and accurate 3D human representations.