Fine Grained 3D

Fine-grained 3D modeling focuses on creating highly detailed and accurate three-dimensional representations of objects and scenes, surpassing the limitations of coarser methods. Current research emphasizes developing novel algorithms and architectures, such as generative cellular automata, Gaussian splatting, and differentiable ray tracing, to achieve this high level of detail from various input sources including monocular videos, sparse LiDAR scans, and even mmWave sensor data. These advancements are crucial for applications ranging from autonomous vehicle navigation and robotics to virtual and augmented reality, enabling more realistic and interactive experiences. The incorporation of semantic information and geometric priors further enhances the accuracy and efficiency of these models.