PLSR: Progressive and Localized Super-Resolution of 3D Objects via Localized Latent Voxel Diffusion
High-resolution 3D asset generation is vital in various 3D applications. Existing state-of-the-art diffusion-based models remain constrained by fixed resolutions, limiting their ability to produce details. In this paper, we tackle the challenge of generating more detailed, higher-resolution 3D objects by introducing a 3D super-resolution (SR) framework built on existing 3D generative foundation models. To this end, we design PLSR, a progressive and localized super-resolution solution to achieve this goal effectively and memory efficiently. Technically, given a coarse geometry from a pretrained 3D generator, we decompose the global SR task into localized sub-tasks via an associative input ...
| Authors | Yuxin Liu, Minshan Xie, Jiawen Liang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 6 September 2026 |
| Last updated at source | 25 September 2026 |
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