{"url":"/method/imghum","slug":"imghum","name":"imGHUM","full_name":"imGHUM","full_name_withheld":false,"description_markdown":"**imGHUM** is a generative model of 3D human shape and articulated pose, represented as a signed distance function. The full body is modeled implicitly as a function zero-level-set and without the use of an explicit template mesh. We compute the signed distance $s = S\\left(\\rho, \\alpha\\right)$ and the semantics $c = C\\left(\\rho, \\alpha\\right)$ of a spatial point $\\rho$ to the surface of an articulated human shape defined by the generative latent code $\\alpha$. Using an explicit skeleton, we transform the point $\\rho$ into the normalized coordinate frames as {$\\tilde{\\rho}^{j}$} for $N = 4$ sub-part networks, modeling body, hands, and head. Each sub-model {$S^{j}$} represents a semantic signed-distance function. The sub-models are finally combined consistently using an MLP U to compute the outputs $s$ and $c$ for the full body. The multi-part pipeline builds a full body model as well as sub-part models for head and hands, jointly, in a consistent training loop. \r\n\r\nOn the right of the Figure, we visualize the zero-level-set body surface extracted with marching cubes and the implicit correspondences to a canonical instance given by the output semantics. The semantics allows e.g. for surface coloring or texturing.","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":"https://arxiv.org/abs/2108.10842v1","title":"imGHUM: Implicit Generative Models of 3D Human Shape and Articulated Pose","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"3D Representations","url":"/methods/category/3d-representations","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":null,"papers_newest_first":[{"paper":"/paper/imghum-implicit-generative-models-of-3d-human","title":"imGHUM: Implicit Generative Models of 3D Human Shape and Articulated Pose","date":"2021-08-24","arxiv_id":"2108.10842","n_code_links":1,"syntology":null}],"papers_shown":1,"tasks":[],"tasks_shown":0,"n_tasks":0,"usage_by_year":[{"year":"2021","papers":1}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/imghum"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}