NeRF Transformation

NeRF transformation focuses on modifying and enhancing neural radiance fields (NeRFs), 3D scene representations enabling realistic novel view synthesis. Current research emphasizes improving NeRF robustness to real-world variations (e.g., lighting changes, object movement) through techniques like point-wise parameter adaptation and incorporating uncertainty modeling. Significant efforts also target efficient editing and manipulation of NeRFs, including local modifications guided by multimodal inputs (text, images, 3D models) and seamless merging of multiple NeRFs. These advancements are crucial for expanding NeRF applications in areas like augmented reality, autonomous driving, and large-scale 3D scene reconstruction.