3 citations · 5 across the 13 of their papers we have counts for
4 papers · 1 filter
Learning 3D Editing without Paired Supervision via Generative Prior Distillation
Hao Wen, Weibin Yun, Hongxing Fan +4
Instruction-guided 3D editing is essential for interactive content creation, yet it faces a significant bottleneck: the severe scarcity of high-quality paired training data. Existi…
Repurposing 3D Generative Model for Autoregressive Layout Generation
Haoran Feng, Yifan Niu, Zehuan Huang +3
We introduce LaviGen, a framework that repurposes 3D generative models for 3D layout generation. Unlike previous methods that infer object layouts from textual descriptions, LaviGe…
PROMO: Promptable Outfitting for Efficient High-Fidelity Virtual Try-On
Haohua Chen, Tianze Zhou, Wei Zhu +8
Virtual Try-on (VTON) has become a core capability for online retail, where realistic try-on results provide reliable fit guidance, reduce returns, and benefit both consumers and m…
SegviGen: Repurposing 3D Generative Model for Part Segmentation
Lin Li, Haoran Feng, Zehuan Huang +8
We introduce SegviGen, a framework that repurposes native 3D generative models for 3D part segmentation. Existing pipelines either lift strong 2D priors into 3D via distillation or…