3D Human Mesh Modeling and Recovery from RGB and LiDAR

The understanding of human pose and shape is the cornerstone of multiple AI applications ranging from monitoring, AR/VR, sport and posture analysis, human-robot interaction all the way to autonomous driving. Accurate human perception enables digital systems to interact appropriately with people in both indoor and outdoor environments.Recent advances have pushed the field forward: modern methods now begin to achieve strong in-the-wild Human Mesh Recovery (HMR) performance, making them more reliable and useful for a wide variety of downstream tasks. With this growing interest, the community has seen the emergence of datasets and shape-recovery models, as well as an expanding range of input modalities; including RGB, depth, LiDAR, etc. At the same time, multiple human body models are being developed, each offering different levels of detail, interpretability and expressivity.While these developments open up exciting new opportunities, they also introduce new challenges. Designing and deploying human mesh recovery systems remains difficult due to dependency on the chosen body model, peculiarities of single-person and multi-person settings, challenges of occlusions and interactions with the 3D scene, and the reliance on data-hungry training pipelines.This tutorial is therefore motivated by the need for a clear, structured, and accessible overview of the current HMR landscape. The increasing use of foundation models and large-scale pretrained systems makes it particularly timely to disseminate a clear picture of the underlying principles of human body modeling and HMR, so that these methods can be more easily adopted, extended, and applied to adjacent fields beyond core human pose estimation. Our goal is to lower the entry barrier for newcomers, provide a unifying perspective for practitioners, and foster collaboration between communities working on human modeling, 3D vision, graphics, and embodied AI. By providing access to these concepts, we aim to maximize the impact of recent advances and encourage their use in downstream applications.