A Survey on Text-Driven 360-Degree Panorama Generation

TL;DR

This survey reviews recent advances in text-driven 360-degree panorama generation, highlighting algorithms, related domains, limitations, and future research directions in immersive visual content creation.

Contribution

It provides a comprehensive analysis of state-of-the-art methods and extends discussion to 3D scene and panoramic video generation from text.

Findings

Summarizes key algorithms and techniques in the field.

Identifies current limitations and challenges.

Suggests promising future research directions.

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/.