RenderFormer: How neural networks are reshaping 3D rendering
RenderFormer: How neural networks are reshaping 3D rendering
“3D rendering—the process of converting three-dimensional models into two-dimensional images—is a foundational technology in computer graphics, widely used across gaming, film, virtual reality, and architectural visualization. Traditionally, this process has depended on physics-based techniques like ray tracing and rasterization, which simulate light behavior through mathematical formulas and expert-designed models.
Now, thanks to advances in AI, especially neural networks, researchers are beginning to replace these conventional approaches with machine learning (ML). This shift is giving rise to a new field known as neural rendering.
Neural rendering combines deep learning with traditional graphics techniques, allowing models to simulate complex light transport without explicitly modeling physical optics. This approach offers significant advantages: it eliminates the need for handcrafted rules, supports end-to-end training, and can be optimized for specific tasks. Yet, most current neural rendering methods rely on 2D image inputs, lack support for raw 3D geometry and material data, and often require retraining for each new scene—limiting their generalizability…”
Source: www.microsoft.com/en-us/research/blog/renderformer-how-neural-networks-are-reshaping-3d-rendering/