Latent Scene Representation

Latent scene representation focuses on creating compact, efficient data structures that capture the essential information of a 3D scene, enabling tasks like novel view synthesis, scene forecasting, and reinforcement learning in robotics and autonomous driving. Current research emphasizes using neural networks, particularly transformers and neural radiance fields (NeRFs), often incorporating probabilistic methods to handle uncertainty and improve sample efficiency. These advancements are improving the performance of applications requiring scene understanding, such as autonomous navigation and drug discovery, by enabling more efficient and robust decision-making based on learned scene representations.