Scene Completion

Scene completion aims to reconstruct missing or incomplete parts of a 3D scene from partial observations, such as sparse point clouds or limited viewpoints. Current research focuses on developing robust and efficient algorithms, often employing neural radiance fields (NeRFs), diffusion models, and Gaussian-based methods, to achieve high-fidelity scene reconstruction, including accurate geometry and semantic labeling. This field is crucial for advancing robotics, autonomous driving, and virtual/augmented reality applications by enabling more complete and accurate environmental understanding from limited sensor data.