March 18, 2024, 4:44 a.m. | Tao Wu, Xuewei Li, Zhongang Qi, Di Hu, Xintao Wang, Ying Shan, Xi Li

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.10044v1 Announce Type: new
Abstract: Controllable spherical panoramic image generation holds substantial applicative potential across a variety of domains.However, it remains a challenging task due to the inherent spherical distortion and geometry characteristics, resulting in low-quality content generation.In this paper, we introduce a novel framework of SphereDiffusion to address these unique challenges, for better generating high-quality and precisely controllable spherical panoramic images.For the spherical distortion characteristic, we embed the semantics of the distorted object with text encoding, then explicitly construct …

abstract arxiv challenges content generation cs.cv diffusion diffusion model domains framework geometry however image image generation low novel paper quality resilient type

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