Model overview
GSFixer is a framework designed to improve the quality of 3D Gaussian Splatting (3DGS) representations reconstructed from sparse inputs. It leverages a reference-guided video restoration model built upon a DiT-based video diffusion model (CogVideoX). Reconstructing 3D scenes using 3D Gaussian Splatting (3DGS) from sparse views often results in noticeable artifacts due to insufficient information. GSFixer addresses this challenge by using a reference-guided video restoration approach. By integrating both 2D semantic features (from DINOv2) and 3D geometric features (from VGGT) of reference views, the model enhances semantic coherence and 3D consistency when fixing novel views rendered from low-quality 3DGS.
Key features
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Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
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| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
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Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
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Sources & traceability
许可证:来源未披露,须进一步核验。模型介绍与第三方评测均以原来源的具体版本和方法为准。