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Published at May 10Expressive Gaussian Human Avatars from Monocular RGB Video
NeurIPS
Released Date: May 10, 2024
Authors: Hezhen Hu1, Zhiwen Fan1, Tianhao Walter Wu, Yihan Xi1, Seoyoung Lee1, Georgios Pavlakos1, Zhangyang Wang1
Aff.: 1University of Texas at Austin
Arxiv: https://openreview.net/pdf/d3eeb6925f27576c641205c98103704bbe8e32eb.pdf

| Method | N-GS | Full | Hand | Face | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| PSNR | SSIM | LPIPS | PSNR | SSIM | LPIPS | PSNR | SSIM | LPIPS | ||
| Controlled setting: XHumans dataset | ||||||||||
| 3DGS [20] + SMPLX | 19,458 | 28.88 | 0.9609 | 44.93 | 25.28 | 0.9189 | 91.37 | 25.91 | 0.9087 | 101.04 |
| GART [23] + SMPLX | 89,571 | 27.73 | 0.9553 | 50.32 | 25.42 | 0.9151 | 99.53 | 25.86 | 0.9013 | 105.06 |
| GauHuman [12] + SMPLX | 17,134 | 29.16 | 0.9623 | 41.16 | 25.69 | 0.9225 | 88.16 | 26.27 | 0.9124 | 93.35 |
| EVA | 19,993 | 29.67 | 0.9632 | 33.05 | 26.27 | 0.9279 | 72.95 | 26.56 | 0.9157 | 72.30 |
| Real-world setting: UPB dataset | ||||||||||
| 3DGS [20] + SMPLX | 21,008 | 25.31 | 0.9469 | 90.80 | 24.89 | 0.9425 | 66.19 | 24.57 | 0.9072 | 136.53 |
| GART [23] + SMPLX | 90,676 | 26.20 | 0.9511 | 78.90 | 25.25 | 0.9411 | 61.44 | 26.62 | 0.9253 | 93.28 |
| GauHuman [12] + SMPLX | 12,372 | 25.17 | 0.9455 | 84.87 | 24.67 | 0.9418 | 67.61 | 24.33 | 0.9035 | 113.13 |
| EVA | 20,829 | 26.78 | 0.9519 | 65.07 | 27.00 | 0.9524 | 45.90 | 26.85 | 0.9298 | 65.90 |