We present a suite of techniques for jointly optimizing triangle meshes and
shading models to match the appearance of reference scenes. This capability has
a number of uses, including appearance-preserving simplification of extremely
complex assets, conversion between rendering systems, and even conversion
between geometric scene representations.
We follow and extend the classic analysis-by-synthesis family of techniques:
enabled by a highly efficient differentiable renderer and modern nonlinear
optimization algorithms, our results are driven to minimize the image-space
difference to the target scene when rendered in similar viewing and lighting
conditions. As the only signals driving the optimization are differences in
rendered images, the approach is highly general and versatile: it easily
supports many different forward rendering models such as normal mapping,
spatially-varying BRDFs, displacement mapping, etc. Supervision through images
only is also key to the ability to easily convert between rendering systems and
scene representations.
We output triangle meshes with textured materials to ensure that the models
render efficiently on modern graphics hardware and benefit from, e.g.,
hardware-accelerated rasterization, ray tracing, and filtered texture lookups.
Our system is integrated in a small Python code base, and can be applied at
high resolutions and on large models. We describe several use cases, including
mesh decimation, level of detail generation, seamless mesh filtering and
approximations of aggregate geometry.

本文提出了一套技术来同时优化三角形网格和着色模型，以匹配参考场景的外观，从而实现外观保持的简化，渲染系统之间及几何场景之间的转换。通过高度有效的可微渲染器和现代非线性优化算法，将结果驱动到在相似的视角和光照下渲染的目标场景图像空间差异最小。输出带有纹理材料的三角形网格，以保证模型在现代图形硬件上高效渲染，并受益于硬件加速光栅化、射线追踪和过滤纹理查找。