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SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity
April 2, 2024, 7:49 p.m. | Peihao Wang, Zhiwen Fan, Dejia Xu, Dilin Wang, Sreyas Mohan, Forrest Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra
cs.CV updates on arXiv.org arxiv.org
Abstract: Score distillation has emerged as one of the most prevalent approaches for text-to-3D asset synthesis. Essentially, score distillation updates 3D parameters by lifting and back-propagating scores averaged over different views. In this paper, we reveal that the gradient estimation in score distillation is inherent to high variance. Through the lens of variance reduction, the effectiveness of SDS and VSD can be interpreted as applications of various control variates to the Monte Carlo estimator of the …
abstract arxiv cs.cv distillation gradient identity paper parameters synthesis text type updates variance via
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