Bridging Diffusion Models and 3D Representations: A 3D Consistent Super-Resolution Framework

• URL: http://arxiv.org/abs/2508.04090v1
• Date: Wed, 06 Aug 2025 05:12:02 GMT
• Title: Bridging Diffusion Models and 3D Representations: A 3D Consistent Super-Resolution Framework
• Authors: Yi-Ting Chen, Ting-Hsuan Liao, Pengsheng Guo, Alexander Schwing, Jia-Bin Huang,
• Abstract summary: 3D Super Resolution (3DSR)<n>Novel 3D Gaussian-splatting-based super-resolution framework.<n>We evaluate 3DSR on MipNeRF360 and LLFF data.
• Score: 53.251525710625096
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose 3D Super Resolution (3DSR), a novel 3D Gaussian-splatting-based super-resolution framework that leverages off-the-shelf diffusion-based 2D super-resolution models. 3DSR encourages 3D consistency across views via the use of an explicit 3D Gaussian-splatting-based scene representation. This makes the proposed 3DSR different from prior work, such as image upsampling or the use of video super-resolution, which either don't consider 3D consistency or aim to incorporate 3D consistency implicitly. Notably, our method enhances visual quality without additional fine-tuning, ensuring spatial coherence within the reconstructed scene. We evaluate 3DSR on MipNeRF360 and LLFF data, demonstrating that it produces high-resolution results that are visually compelling, while maintaining structural consistency in 3D reconstructions. Code will be released.

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