Novel View Synthesis from a Single RGBD Image for Indoor Scenes. (arXiv:2311.01065v1 [cs.CV])

In this paper, we propose an approach for synthesizing novel view images from
a single RGBD (Red Green Blue-Depth) input. Novel view synthesis (NVS) is an
interesting computer vision task with extensive applications. Methods using
multiple images has been well-studied, exemplary ones include training
scene-specific Neural Radiance Fields (NeRF), or leveraging multi-view stereo
(MVS) and 3D rendering pipelines. However, both are either computationally
intensive or non-generalizable across different scenes, limiting their
practical value. Conversely, the depth information embedded in RGBD …

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