Rapid 3D Reconstruction of E-commerce Product Scenes Based on Neural Radiance Fields

This paper studies the method based on NeRF (Neural Radiance Fields) to achieve rapid and accurate 3D scene reconstruction in e-commerce products. Using the NeRF model, it is possible to infer the 3D geometric structure from 2D images and construct realistic 3D models of goods. This paper uses an improved NeRF method for 3D scene reconstruction, which can effectively shorten the training time. In 3D reconstruction, algorithms based on deep learning have developed rapidly and are widely concerned by researchers for their efficiency and speed. The proposal of NeRF has become the mainstream direction for future 3D reconstruction development. This method does not require complex sensors and can achieve 3D reconstruction by taking pictures with a mobile phone.