What do studio and vendor first-person accounts say about the real speed and accuracy gains of ML deformers in production rigs, and where do they fall short?
DreamWorks and Berkeley (2018) report 5x-10x faster deformation evaluation on production rigs. Golaem (DigiPro 2024) tried to reproduce this in a commercial crowd product and reports only x1.2-x2 on production assets because the paper's rigs were optimised for the model and the rest of rig evaluation dominates; its main disappointment was no significant speed gain. It reports Euler-angle and facial limits of the first method, ships the ML deformer as a crowd-package feature for close-up facial deformation, and notes crowd artists prefer overfitting because crowd sims blend clips rather than generate unseen animation. The paper's own Table 1 fps values imply 1.8x-2.5x, which does not match its text range.
Structured fields
{
"citations": [
{
"url": "https://research.dreamworks.com/wp-content/uploads/2018/08/Rig_Approximation-Edited.pdf",
"note": "Bailey et al. 2018 author-version PDF (equals producer pin): abstract line 24; notice line 32; performance section; arXiv 2406.09783v1 (DigiPro 2024) pdftotext -layout: Sec. 6.4 lines 279-302, Table 1 lines 253-256, Table 2 lines 260-267"
},
{
"url": "https://arxiv.org/abs/2406.09783v1",
"note": "Bailey et al. 2018 author-version PDF (equals producer pin): abstract line 24; notice line 32; performance section; arXiv 2406.09783v1 (DigiPro 2024) pdftotext -layout: Sec. 6.4 lines 279-302, Table 1 lines 253-256, Table 2 lines 260-267"
},
{
"url": "http://web.archive.org/web/20230126203603id_/https://www.unrealengine.com/en-US/blog/battle-testing-unreal-engine-5-1-s-new-features-on-fortnite-battle-royale-chapter-4",
"note": "Bailey et al. 2018 author-version PDF (equals producer pin): abstract line 24; notice line 32; performance section; arXiv 2406.09783v1 (DigiPro 2024) pdftotext -layout: Sec. 6.4 lines 279-302, Table 1 lines 253-256, Table 2 lines 260-267"
}
]
}Evidence claims
- [sourced_fact] DreamWorks and Berkeley (2018) report 5x-10x faster deformation evaluation on production rigs. Golaem (DigiPro 2024) tried to reproduce this in a commercial crowd product and reports only x1.2-x2 on production assets because the paper's rigs were optimised for the model and the rest of rig evaluation dominates; its main disappointment was no significant speed gain. It reports Euler-angle and facial limits of the first method, ships the ML deformer as a crowd-package feature for close-up facial deformation, and notes crowd artists prefer overfitting because crowd sims blend clips rather than generate unseen animation. The paper's own Table 1 fps values imply 1.8x-2.5x, which does not match its text range. · locator: Bailey et al. 2018 author-version PDF (equals producer pin): abstract line 24; notice line 32; performance section; arXiv 2406.09783v1 (DigiPro 2024) pdftotext -layout: Sec. 6.4 lines 279-302, Table 1 lines 253-256, Table 2 lines 260-267 source
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | unknown | permitted | permitted | unknown | unknown | Applies to this original summary only, not to the cited sources. |
Linked records
- cites → http://web.archive.org/web/20230126203603id_/https:/www.unrealengine.com/en-US/blog/battle-testing-unreal-engine-5-1-s-new-features-on-fortnite-battle-royale-chapter-4
- cites → https://arxiv.org/abs/2406.09783v1
- cites → https://research.dreamworks.com/wp-content/uploads/2018/08/Rig_Approximation-Edited.pdf