We introduce the WorldScore benchmark, the first unified benchmark for world generation. We decompose world generation into a sequence of next-scene generation tasks with explicit camera trajectory-based layout specifications, enabling unified evaluation of diverse approaches from 3D and 4D scene generation to video generation models. The WorldScore benchmark encompasses a curated dataset of 3,000 test examples that span diverse worlds: static and dynamic, indoor and outdoor, photorealistic and stylized. The WorldScore metrics evaluate generated worlds through three key aspects: controllability, quality, and dynamics. Through extensive evaluation of 19 representative models, including both open-source and closed-source ones, we reveal key insights and challenges for each category of models. Our dataset, evaluation code, and leaderboard can be found at https://haoyi-duan.github.io/WorldScore/
Cite
@article{arxiv.2504.00983,
title = {WorldScore: A Unified Evaluation Benchmark for World Generation},
author = {Haoyi Duan and Hong-Xing Yu and Sirui Chen and Li Fei-Fei and Jiajun Wu},
journal= {arXiv preprint arXiv:2504.00983},
year = {2025}
}
Comments
ICCV 2025. Project website: https://haoyi-duan.github.io/WorldScore/ The first two authors contributed equally