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FixAnything model refines 3D rendering artifacts using video generative priors

Researchers have developed FixAnything, a novel model designed to refine 3D renderings and fix artifacts across various representations like Gaussian Splatting and NeRF. The model repurposes a pre-trained video generative model, treating rendering cleanup as a video-to-video translation task. By using a binary mask to identify clean pixels and employing Direct Preference Optimization with camera pose accuracy as a reward signal, FixAnything achieves 3D-consistent results with minimal fine-tuning, offering a generalist solution that can replace multiple specialized refinement pipelines. AI

IMPACT This research offers a unified approach to improving 3D rendering quality, potentially streamlining workflows for 3D artists and developers.

RANK_REASON The cluster describes a new research paper detailing a novel model for 3D rendering refinement.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

FixAnything model refines 3D rendering artifacts using video generative priors

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The cluster describes a new research paper detailing a novel model for 3D rendering refinement.
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COVERAGE [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    FixAnything: 3D-Consistent Rendering Refinement via Video Generative Priors

    Rendering views using 3D scene representations such as Gaussian Splatting (3DGS), Neural Radiance Fields (NeRF), meshes, or even point clouds produces artifacts when input views are sparse or target views lie far from the input. Recent work mitigates these artifacts using diffusi…

  2. arXiv cs.CV TIER_1 English(EN) · Khiem Vuong, Deva Ramanan, Srinivasa Narasimhan ·

    FixAnything: 3D-Consistent Rendering Refinement via Video Generative Priors

    arXiv:2608.23549v1 Announce Type: new Abstract: Rendering views using 3D scene representations such as Gaussian Splatting (3DGS), Neural Radiance Fields (NeRF), meshes, or even point clouds produces artifacts when input views are sparse or target views lie far from the input. Rec…