АНАЛІЗ МЕТОДІВ СТВОРЕННЯ 3D МОДЕЛЕЙ ЗА ДОПОМОГОЮ НЕЙРОННИХ МЕРЕЖ

Methods that use neural networks to create 3D models from raw data such as photos or videos are gaining importance. These methods include 3D Convolutional Neural Networks (3D CNNs), Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs) and Neural Radiance Fields (NeRF). Combining these approaches helps overcome existing limitations, enhancing the accuracy and realism of generated models. Innovations like MIT’s Light Field Networks (LFNs) and NVIDIA’s GANverse3D exemplify progress in this field. Сombines the advantages of GAN and NeRF can be offered like own method, which shows good results.