In this paper, we present PanoDreamer, a novel method for producing a coherent 360$^\circ$ 3D scene from a single input image. Unlike existing methods that generate the scene sequentially, we frame the problem as single-image panorama and depth estimation. Once the coherent panoramic image and its corresponding depth are obtained, the scene can be reconstructed by inpainting the small occluded regions and projecting them into 3D space. Our key contribution is formulating single-image panorama and depth estimation as two optimization tasks and introducing alternating minimization strategies to effectively solve their objectives. We demonstrate that our approach outperforms existing techniques in single-image 360$^\circ$ scene reconstruction in terms of consistency and overall quality.

翻译：本文提出PanoDreamer，一种从单张输入图像生成连贯360°三维场景的新方法。与现有顺序生成场景的方法不同，我们将该问题构建为单图像全景图与深度估计任务。在获得连贯的全景图像及其对应深度后，可通过修复小范围遮挡区域并将其投影至三维空间来重建场景。我们的核心贡献在于将单图像全景与深度估计构建为两个优化任务，并引入交替最小化策略以有效求解其目标函数。实验表明，在单图像360°场景重建任务中，本方法在一致性与整体质量方面均优于现有技术。