Explore >> Select a destination

You are here

 belcour.github.io
A Low-Discrepancy Sampler that Distributes Monte Carlo Errors as a Blue Noise in Screen Space
| | psgraphics.blogspot.com
Pete Shirley's Graphics Blog: Flavors of Sampling in Ray Tracing
4.0 parsecs away

Travel
| | Most "ray tracers" these days are what we used to call "path tracers" or "Monte Carlo ray tracers". Because they all have about the same c...
| | momentsingraphics.de
My toy renderer, part 4: Ray tracing
3.3 parsecs away

Travel
| | [AI summary] The text discusses advanced techniques for rendering physically accurate and efficient soft shadows using polygonal and linear lights in real-time ray tracing. It covers methods like projected solid angle sampling, LTC sampling, and MIS heuristics, along with optimizations and applications such as textured lights, IES profiles, and portals. The text also touches on performance considerations and future directions in global illumination.
| | puye.blog
What we talk about when we talk about Ray Tracing? | Puye's Blog
5.2 parsecs away

Travel
| | Let's provide a concise overview of ray tracing. We won't delve into subjects like Monte Carlo and stratified sampling, PBRT, BRDF, rendering equations, denoising techniques, or intricate SDF concepts. In essence, we'll stick to the fundamentals.
| | scorpil.com
Understanding Generative AI: Part Two - Neural Networks ยท Scorpil
15.4 parsecs away

Travel
| In Part One of the "Understanding Generative AI" series, we delved into Tokenization - the process of dividing text into tokens, which serve as the fundamental units of information for neural networks. These tokens are crucial in shaping how AI interprets and processes language. Building upon this foundational knowledge, we are now ready to explore Neural Networks - the cornerstone technology underpinning all Artificial Intelligence research. A Short Look into the History Neural Networks, as a technology, have their roots in the 1940s and 1950s.