Datasets:
DPE codes for all 8 P1-P4 captures; note the P5C2/P6C2 gap
Browse files
README.md
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@@ -485,8 +485,16 @@ convex combination as augmentation.
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| P2C2 | 800 | cam07, cam30 | 200 |
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| P3C1 | 3664 | cam07, cam30 | 916 |
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| 487 |
| P3C2 | 814 | cam07, cam30 | 203 |
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**How they were made.** The code is `mlp_exp(dir(mlp(enc(face_crop))))` from
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[OpenTalker/DPE](https://github.com/OpenTalker/DPE)'s `Generator(size=256, style_dim=512,
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| 485 |
| P2C2 | 800 | cam07, cam30 | 200 |
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| 486 |
| P3C1 | 3664 | cam07, cam30 | 916 |
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| 487 |
| P3C2 | 814 | cam07, cam30 | 203 |
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| P4C1 | 3098 | cam07, cam30 | 774 |
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| 489 |
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| P4C2 | 526 | cam07, cam30 | 131 |
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Counts are codes, not frames: each frame contributes one code per camera, so a capture of
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*N* frames shot with two cameras yields 2*N*.
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**`P5C2` and `P6C2` have no DPE codes.** They are the cross-reenactment driving sequences,
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and only the eight `P1`..`P4` captures were extracted. If you want to drive an avatar with
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`P5C2` or `P6C2` on the DPE path, generate them yourself with `scripts/extract_dpe_codes.py`
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(the command below), or use the SMPL-X path, which needs nothing extra.
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**How they were made.** The code is `mlp_exp(dir(mlp(enc(face_crop))))` from
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[OpenTalker/DPE](https://github.com/OpenTalker/DPE)'s `Generator(size=256, style_dim=512,
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