Semantic Score Distillation Sampling for Compositional Text-to-3D Generation

Understand

Generating high-quality 3D assets from textual descriptions remains a pivotal challenge in computer graphics and vision research.

• Due to the scarcity of 3D data, state-of-the-art approaches utilize pre-trained 2D diffusion priors, optimized through Score Distillation Sampling (SDS).
• Despite progress, crafting complex 3D scenes featuring multiple objects or intricate interactions is still difficult.
• To tackle this, recent methods have incorporated box or layout guidance.