Feb. 9, 2024, 5:46 a.m. | Tianhao Wu Chuanxia Zheng Tat-Jen Cham

cs.CV updates on arXiv.org arxiv.org

Generating complete 360-degree panoramas from narrow field of view images is ongoing research as omnidirectional RGB data is not readily available. Existing GAN-based approaches face some barriers to achieving higher quality output, and have poor generalization performance over different mask types. In this paper, we present our 360-degree indoor RGB-D panorama outpainting model using latent diffusion models (LDM), called PanoDiffusion. We introduce a new bi-modal latent diffusion structure that utilizes both RGB and depth panoramic data during training, which works …

cs.cv data diffusion face gan images narrow outpainting panorama paper performance quality research rgb-d types via view

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