Novel View Synthesis

Novel view synthesis (NVS) aims to generate realistic images from viewpoints not directly captured, reconstructing 3D scenes from 2D data. Current research heavily utilizes implicit neural representations, such as neural radiance fields (NeRFs) and 3D Gaussian splatting, focusing on improving efficiency, handling sparse or noisy input data (including single-view scenarios), and enhancing the realism of synthesized views, particularly for complex scenes with dynamic elements or challenging lighting conditions. These advancements have significant implications for various fields, including robotics, cultural heritage preservation, and virtual/augmented reality applications, by enabling more accurate 3D modeling and more immersive experiences.