Sim2real transfer learning for 3D human pose estimation: motion to the rescue
Synthetic visual data can provide practicically infinite diversity and rich labels, while avoiding ethical issues with privacy and bias. However, for many tasks, current models trained on synthetic data generalize poorly to real data. The task of 3D human pose estimation is a particularly interestin...
| Main Authors: | , |
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| Format: | Conference item |
| Language: | English |
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Curran Associates
2020
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