PLSR: Progressive and Localized Super-Resolution of 3D Objects via Localized Latent Voxel Diffusion

• URL: http://arxiv.org/abs/2609.06436v1
• Date: Sun, 06 Sep 2026 07:21:36 GMT
• Title: PLSR: Progressive and Localized Super-Resolution of 3D Objects via Localized Latent Voxel Diffusion
• Abstract summary: High-resolution 3D asset generation is vital in various 3D applications.<n>Existing state-of-the-art diffusion-based models remain constrained by fixed resolutions.<n>We introduce a 3D super-resolution framework built on existing 3D generative foundation models.
• Score: 44.63283515238481
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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 decomposition scheme, adapt a flow-based 3D generator into a localized super-resolution model through low-cost finetuning, and unify them in an iterative patch-wise denoising pipeline for seamless high-resolution output. Experiments on challenging objects show that our approach is able to generate 3D details with new strong fine-detail fidelity while significantly reducing the computational cost, offering a new and practical solution for high-resolution 3D asset generation.

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