# Better Together: Unified Motion Capture and 3D Avatar Reconstruction

arXiv: https://arxiv.org/abs/2503.09293 · HTML: https://mlsanity.com/paper/2503.09293/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- First posted on arXiv 12 Mar 2025.

## Abstract (arXiv)

We present Better Together, a method that simultaneously solves the human pose estimation problem while reconstructing a photorealistic 3D human avatar from multi-view videos. While prior art usually solves these problems separately, we argue that joint optimization of skeletal motion with a 3D renderable body model brings synergistic effects, i.e. yields more precise motion capture and improved visual quality of real-time rendering of avatars. To achieve this, we introduce a novel animatable avatar with 3D Gaussians rigged on a personalized mesh and propose to optimize the motion sequence with time-dependent MLPs that provide accurate and temporally consistent pose estimates. We first evaluate our method on highly challenging yoga poses and demonstrate state-of-the-art accuracy on multi-view human pose estimation, reducing error by 35% on body joints and 45% on hand joints compared to keypoint-based methods. At the same time, our method significantly boosts the visual quality of animatable avatars (+2dB PSNR on novel view synthesis) on diverse challenging subjects.