Erp-Aware Text-To-360 Panorama Diffusion Model

Growing demand for immersive media and virtual reality highlights the importance of text-to-360° panoramic image (T2P) generation. While diffusion models have achieved remarkable success in image generation, generating equirectangular projection (ERP) images from text is challenging due to spherical projection distortion and the lack of sufficient ERP data to establish clear priors during training. In contrast, cube-map perspective views, a standard 2D image trained on abundant text-image pairs, provide stable generation results. In this paper, we propose a novel T2P model, consisting of an ERP-aware diffusion process in the forward direction and a perspective-aware diffusion process in the reverse direction, supported by several enabling modules to bridge the domain gap between ERP and 2D images. Experimental results demonstrate that the proposed model effectively generates visually compelling and high-quality ERP images while maintaining realistic patterns in ERP.