DF3DV-1K: A Large-Scale Dataset and Benchmark for Distractor-Free Novel View Synthesis
A large-scale real-world dataset called DF3DV-1K is introduced to address the lack of clean and cluttered image sets for distractor-free radiance field research, containing 1,048 s…
Hugging Face · Daily Papers
·Cheng-You Lu, Yi-Shan Hung
·
·▲ 31 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Cheng-You Lu, Yi-Shan Hung, Wei-Ling Chi, Hao-Ping Wang, Charlie Li-Ting Tsai, Yu-Cheng Chang
- 31 upvotes da comunidade
- Temas: radiance fields, distractor-free, novel view synthesis, diffusion-based 2D enhancer, 3D Gaussian Splatting, PSNR
Resumo
Resumo original (em inglês), extraído do paper:
A large-scale real-world dataset called DF3DV-1K is introduced to address the lack of clean and cluttered image sets for distractor-free radiance field research, containing 1,048 scenes with 89,924 images across 128 distractor types and 161 scene themes, along with a curated subset DF3DV-41 for robustness evaluation, and demonstrates improved performance when used to fine-tune a diffusion-based 2D enhancer for radiance field methods.
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