Consistent 3D

Consistent 3D research focuses on generating and manipulating realistic three-dimensional models from limited data, aiming for accurate geometric and visual consistency across different viewpoints and modalities (e.g., images, LiDAR). Current efforts leverage techniques like diffusion models, generative Gaussian splatting, and geometric optimization algorithms, often incorporating multi-view consistency constraints and case-aware mechanisms to improve generalization and accuracy. This work has significant implications for various fields, including autonomous driving, virtual/augmented reality, and biodiversity conservation, by enabling the creation of high-quality 3D assets and facilitating more accurate scene understanding from incomplete information.