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This document presents Deceptive-NeRF/3DGS, a novel approach to enhance sparse-view reconstruction using diffusion-generated pseudo-observations. The method leverages a pre-trained diffusion model to directly generate high-quality images from few-view reconstructions, significantly improving the reconstruction process in settings with limited input images. This approach not only enhances the quality of synthesized novel views but also reduces the amount of time and computational power...
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Deceptive-nerf3dgs refers to a regulatory form or document used to report various types of deceptive practices in business or marketing.
Businesses or individuals engaged in practices that could be classified as deceptive are typically required to file the deceptive-nerf3dgs.
To fill out the deceptive-nerf3dgs, one must provide accurate information regarding the deceptive practices, including details about the entities involved and the nature of the deception.
The purpose of deceptive-nerf3dgs is to ensure transparency and compliance with legal standards regarding honest business practices.
The report must include details such as the nature of the deception, the parties involved, dates of occurrence, and any corrective actions taken.
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