A Gpu-based solution for large-scale skeletal animation simulation

Xi Pan

Home/Archive/arXiv

arXiv · 2505.06703

A Gpu-based solution for large-scale skeletal animation simulation

Xi Pan

View original source ↗Read source document ↗Export metadata ↓

Abstract

Skeletal animations of large-scale characters are widely used in video games. However, with a large number of characters are involved, relying on the CPU to calculate skeletal animations leads to significant performance problems. There are two main types of traditional GPU- based solutions. One is referred to as pre-baked animation texture technology. The problem with this solution is that it can only play animations from the pre-baked animation. It is impossible to perform interpolation, blending and other calculations on the animation, which affects the quality of the animations. The other solution is referred to as dedicated processing with a simple skeleton hierarchy (the number of skeleton levels < 64). This option does not need to simulate and bake animation data in advance. However, performance is dramatically impaired when processing complex skeletons with too many skeleton levels (such as fluttering clothing, soft plants, dragon-like creatures, etc.). In order to solve these issues, we developed a parallel prefix tree update solution to optimize the animation update process of complex skeletons with too many levels, and combined traditional solutions to implement a GPU-based skeletal animation solution. This solution does not need to simulate and bake animation results. In addition, the performance is superior to traditional solutions for complex skeletons with too many levels. Our work can provide a new option for optimizing the performance of large-scale skeletal animation simulations, providing GPU-based skeletal animations a wider range of application scenarios.

Explore related subjects

cs.GR

Keep this discovery

BibTeX RIS

Xi Pan. 2025-05-10. A Gpu-based solution for large-scale skeletal animation simulation. https://arxiv.org/abs/2505.06703

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

ReCHOIR: Contact-guided Human Object Interaction Retargeting to Diverse Characters

We present ReCHOIR, a novel contact-guided motion retargeting method for transferring human object interaction (HOI) motions across diverse humanoid characters. Unlike prior motion retargeting methods that primarily focus on transferring human motion alone, our goal is to preserve not only the semantics of the original body movement but also consistent interaction between the character and the manipulated object, while jointly producing aligned target human and object motions. Given source HOI motion, object geometry, and contact cues extracted from the source interaction, ReCHOIR retargets an HOI sequence to target characters with different skeletal configurations while maintaining both motion semantics and contact-consistent interaction patterns. Our method builds on a Part-Aware Motion Embedding (PAME) autoencoder, which encodes full-body motion into a shared body-part-wise latent space. This representation enables generalization across heterogeneous skeletons while preserving local motion semantics beneficial for part-aware adaptation in HOI retargeting. On top of this representation, we introduce a contact-guided retargeting module and an object motion decoder for HOI retargeting. The contact-guided retargeting module treats the source object interaction as a condition for refining target character motion: object- and contact-related signals are encoded into a body-part-aligned latent representation and injected into decoding through a residual control branch, enabling stronger adaptation in interaction-relevant body regions without discarding the underlying motion prior. In parallel, the object motion decoder predicts a target object motion aligned with the refined target character motion, ensuring that the object trajectory remains consistent with how the interaction is realized by the target character.

cs.GR↗

arXiv2026

Gaussian Light Transport

We present a novel method for computing global illumination by expressing the solution to the light transport equation as a 13D Gaussian mixture model over positions, directions, surface normals, and material properties. We show that including scene properties in the Gaussian representation drastically reduces the number of functions and speeds up evaluation. As opposed to traditional light transport methods based on Neumann series, the parameters of our model are directly estimated by minimizing the residual of the rendering equation. While both optimization and rendering require repeated evaluations of a linear combination of high-dimensional Gaussian functions, we introduce an efficient culling strategy to keep the optimization tractable and produce renderings in real time. Our representation enables to render fast, view-independent solutions to the light transport equation, achieving rendering times on the order of milliseconds, with a fraction of the memory requirements of conventional neural rendering approaches.

cs.GR↗

arXiv2026

Hologram Representation via Quadratic Phase Gaussian Splatting

We introduce Complex-Valued Quadratic Phase Gaussian (CVQPG), a novel hologram representation method that replaces standard 2D Gaussian representations used in 2D Gaussian Splatting with 2D quadratic phase functions. CVQPG incorporates additional learnable parameters to control the curvature of these bases. We evaluate our approach against state-of-the-art methods, exceeding the visual quality by +0.19 dB (RGB) and +0.33 dB (grayscale) on average in holographic reconstructions. Specifically, our equal parameter count evaluations show that modulating the primitive's wavefront is an effective and lightweight enhancement for hologram representations. In addition, our frequency domain analysis illustrates that CVQPG has successfully preserved the mid-to-high frequency band of natural images.

cs.GR↗