Learning 3D editing without paired supervision via generative prior distillation
Hao Wen · hf · 2026-09-09
A new Hugging Face paper presents a feed-forward 3D editing framework that distills visual, semantic, and geometric priors from foundation models via differentiable rendering and 3D-aware distribution matching, removing the need for paired training data—a practical route for 3D editing tasks where paired supervision is scarce.
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