Make-A-Video3D (MAV3D)

Make-A-Video3D (MAV3D) represents a paradigm shift in generative AI, transitioning from flat video generation to full 4D (dynamic 3D) scene synthesis. Developed by Meta AI Research, MAV3D leverages a pre-trained 2D text-to-video model and a 3D scene representation based on Neural Radiance Fields (NeRF). By utilizing Score Distillation Sampling (SDS), the system optimizes a dynamic NeRF to produce high-fidelity, 360-degree navigable scenes that evolve over time based on natural language prompts. This technical architecture bypasses the need for massive 4D datasets, which are historically scarce, by distilling knowledge from established 2D video diffusion models. In the 2026 market, MAV3D serves as a foundational framework for developers in the spatial computing, VR/AR, and gaming industries, enabling the rapid prototyping of animated assets that maintain geometric consistency across all viewing angles. It is positioned as a critical R&D tool for creators building immersive environments within the Meta ecosystem and beyond, pushing the boundaries of what is possible in automated digital twin production and cinematic visual effects.