mlsanityData to 14 Oct 2026

PhoMoH: Implicit Photorealistic 3D Models of Human Heads

arXiv 2212.07275 ↗First posted 14 Dec 2022cs.CVcited by 7

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Abstract (arXiv)

We present PhoMoH, a neural network methodology to construct generative models of photo-realistic 3D geometry and appearance of human heads including hair, beards, an oral cavity, and clothing. In contrast to prior work, PhoMoH models the human head using neural fields, thus supporting complex topology. Instead of learning a head model from scratch, we propose to augment an existing expressive head model with new features. Concretely, we learn a highly detailed geometry network layered on top of a mid-resolution head model together with a detailed, local geometry-aware, and disentangled color field. Our proposed architecture allows us to learn photo-realistic human head models from relatively little data. The learned generative geometry and appearance networks can be sampled individually and enable the creation of diverse and realistic human heads. Extensive experiments validate our method qualitatively and across different metrics.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 52 of its 82 references that are in the map. First posted on arXiv 14 Dec 2022.

Builds on

52 of 82 references.

References · 52

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38 more
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50 most cited of 52 All 52 (JSON)

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Cited by year

Citing papers per year: 2023: 4; 2024: 1; 2025: 2.

7 papers.

  1. 2023MonoNPHM: Dynamic Head Reconstruction from Monocular Videoscited by 35
  2. 2024SphereHead: Stable 3D Full-head Synthesis with Spherical Tri-plane Representationcited by 30
  3. 2023Single-Shot Implicit Morphable Faces with Consistent Texture Parameterizationcited by 16
  4. 2025PanoLAM: Large Avatar Model for Gaussian Full-Head Synthesis from One-shot Unposed Imagecited by 7
  5. 2025HyPlaneHead: Rethinking Tri-plane-like Representations in Full-Head Image Synthesiscited by 6
  6. 2023HeadCraft: Modeling High-Detail Shape Variations for Animated 3DMMscited by 5
  7. 2023SPHEAR: Spherical Head Registration for Complete Statistical 3D Modelingcited by 0