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RenderFormer: Neural rendering of triangle meshes with global illumination
We present RenderFormer, a neural rendering pipeline that directly renders an image from a triangle-based representation of scene with full global illumination effects, and that does not require per-scene training or finetuning.
We present RenderFormer, a neural rendering pipeline that directly renders an image from a triangle-based representation of a scene with full global illumination effects and that does not require per-scene training or fine-tuning. Instead of taking a physics-centric approach to rendering, we formulate rendering as a sequence-to-sequence transformation where a sequence of tokens representing triangles with reflectance properties is converted to a sequence of output tokens representing small patches of pixels. Both stages are based on the transformer architecture and are learned with minimal prior constraints.
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