ProgressiveAvatars: Progressive Animatable 3D Gaussian Avatars

Fuente: arXiv
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Main Authors: Song, Kaiwen, Cui, Jinkai, Zhang, Juyong
Format: Preprint
Published: 2026
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author Song, Kaiwen
Cui, Jinkai
Zhang, Juyong
author_facet Song, Kaiwen
Cui, Jinkai
Zhang, Juyong
contents In practical real-time XR and telepresence applications, network and computing resources fluctuate frequently. Therefore, a progressive 3D representation is needed. To this end, we propose ProgressiveAvatars, a progressive avatar representation built on a hierarchy of 3D Gaussians grown by adaptive implicit subdivision on a template mesh. 3D Gaussians are defined in face-local coordinates to remain animatable under varying expressions and head motion across multiple detail levels. The hierarchy expands when screen-space signals indicate a lack of detail, allocating resources to important areas. Leveraging importance ranking, ProgressiveAvatars supports incremental loading and rendering, adding new Gaussians as they arrive while preserving previous content, thus achieving smooth quality improvements across varying bandwidths. ProgressiveAvatars enables progressive delivery and progressive rendering under fluctuating network bandwidth and varying compute and memory resources.
format Preprint
id arxiv_https___arxiv_org_abs_2603_16447
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle ProgressiveAvatars: Progressive Animatable 3D Gaussian Avatars
Song, Kaiwen
Cui, Jinkai
Zhang, Juyong
Computer Vision and Pattern Recognition
Graphics
In practical real-time XR and telepresence applications, network and computing resources fluctuate frequently. Therefore, a progressive 3D representation is needed. To this end, we propose ProgressiveAvatars, a progressive avatar representation built on a hierarchy of 3D Gaussians grown by adaptive implicit subdivision on a template mesh. 3D Gaussians are defined in face-local coordinates to remain animatable under varying expressions and head motion across multiple detail levels. The hierarchy expands when screen-space signals indicate a lack of detail, allocating resources to important areas. Leveraging importance ranking, ProgressiveAvatars supports incremental loading and rendering, adding new Gaussians as they arrive while preserving previous content, thus achieving smooth quality improvements across varying bandwidths. ProgressiveAvatars enables progressive delivery and progressive rendering under fluctuating network bandwidth and varying compute and memory resources.
title ProgressiveAvatars: Progressive Animatable 3D Gaussian Avatars
topic Computer Vision and Pattern Recognition
Graphics
url https://arxiv.org/abs/2603.16447