mlsanityData to 14 Oct 2026

How to Build Digital Humans? From Priors to Photorealistic Avatars

arXiv 2607.04341 ↗First posted 5 Jul 2026cs.GR cs.CL cs.CVcited by 1

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Abstract (arXiv)

This state-of-the-art report provides an overview of controllable 3D human avatar creation. We describe current 3D avatar systems, which typically consist of three stages: (i) learning priors of human appearance and motion, (ii) creating a personalized avatar, and (iii) animating the avatar. To limit the scope, we focus on the prior learning and avatar creation stages. We define current avatar representations and introduce a taxonomy that categorizes existing work along multiple axes, including body regions and employed priors. We review methods for full-body and head avatars, as well as layered representations that decompose the body into components such as hands, hair, and garments. Finally, we outline common underlying principles, reference key literature for newcomers, and discuss open challenges and future research directions.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 10 of its 575 references that are in the map. First posted on arXiv 5 Jul 2026.

Builds on

10 of 575 references.

References · 10

  1. 2024HunyuanVideo: A Systematic Framework For Large Video Generative Modelscited by 1,660
  2. 2022CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformerscited by 985
  3. 2023Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animationcited by 688
  4. 2024LTX-Video: Realtime Video Latent Diffusioncited by 581
  5. 2025Embodied AI Agents: Modeling the Worldcited by 61
  6. 2025Seamless Interaction: Dyadic Audiovisual Motion Modeling and Large-Scale Datasetcited by 40
  7. 2026Avatar Forcing: Real-Time Interactive Head Avatar Generation for Natural Conversationcited by 19
  8. 2025RealisMotion: Decomposed Human Motion Control and Video Generation in the World Spacecited by 12
  9. 2025DisMo: Disentangled Motion Representations for Open-World Motion Transfercited by 10
  10. 2025AdaViewPlanner: Adapting Video Diffusion Models for Viewpoint Planning in 4D Scenescited by 4

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