Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Modular Primitives for High-Performance Differentiable Rendering   We present a modular differentiable renderer design that yields performance
superior to previous methods by leveraging existing, highly optimized hardware
graphics pipelines. Our design supports all crucial operations in a modern
graphics pipeline: rasterizing large numbers of triangles, attribute
interpolation, filtered texture lookups, as well as user-programmable shading
and geometry processing, all in high resolutions. Our modular primitives allow
custom, high-performance graphics pipelines to be built directly within
automatic differentiation frameworks such as PyTorch or TensorFlow. As a
motivating application, we formulate facial performance capture as an inverse
rendering problem and show that it can be solved efficiently using our tools.
Our results indicate that this simple and straightforward approach achieves
excellent geometric correspondence between rendered results and reference
imagery.

35
The categories of this paper are: mtrl-th
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph