Transparent Surface

Transparent surface representation and rendering are active research areas, focusing on accurately modeling the complex light interactions inherent in these surfaces. Current efforts leverage neural radiance fields (NeRFs) and implicit surface representations, often incorporating techniques like attention mechanisms and learnable embeddings to improve rendering quality and address limitations in handling refraction and semi-transparency. These advancements are crucial for improving 3D scene reconstruction and novel view synthesis, with applications ranging from robotics and augmented reality to computer graphics and material science. The development of benchmark datasets with high-resolution ground truth data is also driving progress in this field.