3D Reconstruction Task

3D reconstruction aims to create three-dimensional models from various input data, such as images, videos, or point clouds. Current research focuses on improving accuracy and robustness, particularly when dealing with sparse, noisy, or incomplete data, employing techniques like neural radiance fields (NeRFs), signed distance fields (SDFs), diffusion models, and vision transformers (ViTs) to achieve this. These advancements are driving progress in diverse fields, including robotics (e.g., autonomous navigation and manipulation), augmented/virtual reality, and remote sensing (e.g., satellite imaging). The development of efficient algorithms and architectures, such as those incorporating Bayesian inference or differentiable physics, is crucial for real-time applications and handling complex scenes.