CREATING 3D SHAPES FROM 2D IMAGES AND TEXTS

Summary from the TLDR AI newsletter

This project introduces a method to generate 3D shapes from 2D images or texts, reducing inconsistencies that result from the dimensional differences. The method uses a two-model framework, the Shape-Image-Text-Aligned Variational Auto-Encoder (SITA-VAE) and Aligned Shape Latent Diffusion Model (ASLDM), to map the 3D shapes into a space that aligns with images and texts.