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WonderJourney: Going from Anywhere to Everywhere

About

We introduce WonderJourney, a modularized framework for perpetual 3D scene generation. Unlike prior work on view generation that focuses on a single type of scenes, we start at any user-provided location (by a text description or an image) and generate a journey through a long sequence of diverse yet coherently connected 3D scenes. We leverage an LLM to generate textual descriptions of the scenes in this journey, a text-driven point cloud generation pipeline to make a compelling and coherent sequence of 3D scenes, and a large VLM to verify the generated scenes. We show compelling, diverse visual results across various scene types and styles, forming imaginary "wonderjourneys". Project website: https://kovenyu.com/WonderJourney/

Hong-Xing Yu, Haoyi Duan, Junhwa Hur, Kyle Sargent, Michael Rubinstein, William T. Freeman, Forrester Cole, Deqing Sun, Noah Snavely, Jiajun Wu, Charles Herrmann• 2023

Related benchmarks

TaskDatasetResultRank
3D Scene GenerationWorldScore
Camera Control84.6
33
Video GenerationWorldScore (test)
Average Score54.19
12
3D Scene GenerationCustom 3D Scene Generation 28 scenes (test)
Time Cost (s)749.5
4
Novel View Rendering28 scenes (city, campus, nature, fantasy) (test)
CS Score27.34
4
Perpetual 3D Scene GenerationCustom Nature Evaluation Set
Diversity92.7
1
Perpetual 3D Scene GenerationCustom Multi-style Text-based Evaluation Set
Diversity88.8
1
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