A Survey on Text-Driven 360-Degree Panorama Generation

Hai Wang, Xiaoyu Xiang, Weihao Xia, Jing-Hao Xue
2/20/2025
cs.CVcs.AI

No official code found. Best implementation: littlewhitesea/Text-Driven-Pano-Gen (41 stars, last commit 2025-11-05).

Abstract

The advent of text-driven 360-degree panorama generation, enabling the synthesis of 360-degree panoramic images directly from textual descriptions, marks a transformative advancement in immersive visual content creation. This innovation significantly simplifies the traditionally complex process of producing such content. Recent progress in text-to-image diffusion models has accelerated the rapid development in this emerging field. This survey presents a comprehensive review of text-driven 360-degree panorama generation, offering an in-depth analysis of state-of-the-art algorithms. We extend our analysis to two closely related domains: text-driven 360-degree 3D scene generation and text-driven 360-degree panoramic video generation. Furthermore, we critically examine current limitations and propose promising directions for future research. A curated project page with relevant resources and research papers is available at https://littlewhitesea.github.io/Text-Driven-Pano-Gen/.

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[TCSVT 2025] A Survey on Text-Driven 360-Degree Panorama Generation

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Cite this paper

@article{wang2025survey,
  title  = {A Survey on Text-Driven 360-Degree Panorama Generation},
  author = {Hai Wang and Xiaoyu Xiang and Weihao Xia and Jing-Hao Xue},
  year   = {2025},
  eprint = {2502.14799},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2502.14799v3}
}

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