3D and 4D World Modeling: A Survey

arXiv 25.09 2025 47.3 survey

TLDR

A comprehensive survey of 3D and 4D world modeling, providing definitions, taxonomy, datasets, metrics, and applications.

Reasoning

The paper's strength lies in being the first dedicated survey on 3D/4D world modeling, offering a clear taxonomy and systematic summary of datasets and metrics. Its weakness is that it is a survey without novel experiments or methods, and it does not deeply address interactive or RL-specific world models.

Read-first score

Read-first score 47.3, weighted from topical fit, citation, graph, method, reproducibility, and recency signals. Original total remains 37.

Recency 6%

86.7

Uses a gentle age decay so recent papers surface without erasing older foundations. 2025

Reproducibility 18%

Screens links and visible text for paper, code, dataset, artifact, and repository signals. pdf=True; code=True; dataset=False; markers=dataset,github

Methodology quality 18%

Screens visible abstract and analysis fields for experiment, dataset, baseline, metric, and limitation evidence. markers=dataset,evaluation,metric

Topical relevance 29%

52.9

Uses existing LLM keyword relevance scores normalized to 0-100. world model,world simulator,generative world model,interactive world model,video world model,world dynamics prediction,model-based reinforcement learning world model

Citation impact 18%

Uses OpenAlex-shaped citation metadata as a bibliometric attention signal, separate from paper quality. cited_by_count=0

Citation velocity 12%

Citation velocity estimates citations per publication-year to reduce old-paper bias. velocity=0.00

Field roles

FrontierMethodology anchorReproducibility anchor

Rank sensitivity

Stability: volatile; rank range: 717.

Keyword Scores

world model

generative world model

video world model

world dynamics prediction

world simulator

interactive world model

model-based reinforcement learning world model

Deep Analysis

Innovations

First comprehensive review explicitly dedicated to 3D and 4D world modeling and generation
Establishment of precise definitions for world models in 3D/4D contexts
Introduction of a structured taxonomy spanning VideoGen, OccGen, and LiDARGen approaches
Systematic summary of datasets and evaluation metrics tailored to 3D/4D settings

Methodology

This survey conducts a comprehensive literature review of 3D and 4D world modeling, establishing precise definitions and a structured taxonomy (VideoGen, OccGen, LiDARGen). It systematically summarizes datasets and evaluation metrics, and discusses applications, open challenges, and future directions.

Key Results

The survey identifies open challenges and highlights promising research directions for 3D/4D world modeling, providing a foundational reference for the field.

Resources

Paper Code