README.md

metadata

pipeline_tag: image-to-image
tags:
  - Novel View Synthesis
  - NeRF
  - 3D Gaussian Splatting
  - Diffusion Models
  - Image Restoration
  - Fixer
  - Distractor

DI²FIX

Project Page | Paper | GitHub | Demo

DI²FIX (Distractor-Free DIFIX) is a plug-and-play 2D enhancer designed to improve radiance field renderings (such as 3D Gaussian Splatting) by removing distractors and artifacts. It was introduced in the paper DF3DV-1K: A Large-Scale Dataset and Benchmark for Distractor-Free Novel View Synthesis.

Method Overview

DI²FIX is a diffusion-based 2D enhancer fine-tuned on the DF3DV-1K dataset. It refines and enhances initial novel-view synthesis outputs, removing distractors and significantly improving rendering quality (achieving average improvements of 0.96 dB PSNR and 0.057 LPIPS on the held-out DF3DV-41 benchmark and the On-the-go dataset).

Citation

@article{lu2026df3dv,
  title={DF3DV-1K: A Large-Scale Dataset and Benchmark for Distractor-Free Novel View Synthesis},
  author={Lu, Cheng-You and Hung, Yi-Shan and Chi, Wei-Ling and Wang, Hao-Ping and Tsai, Charlie Li-Ting and Chang, Yu-Cheng and Liu, Yu-Lun and Do, Thomas and Lin, Chin-Teng},
  journal={arXiv preprint arXiv:2604.13416},
  year={2026}
}