Abstract: The present embodiments generally relate to enhancing a quality of denoising in a real-time pathtracer. A pathtracer can implement a Monte-Carlo process, which can require many samples to converge to an error-acceptable result. Denoisers are often used in real-time (or near real-time), in order to accelerate the convergence process. The present embodiments further comprise systems and methods relating to an adaptive guidance algorithm to be implemented on top of various denoising algorithms (e.g., SVGF/ASVGF). The systems and methods as described herein can improve the gradient estimation quality, producing less blurry images. The systems and methods can also substantially assist many denoising algorithms in complicated illumination scenarios, which are common in CADs, such as indirect illuminated normal maps, specular paths, sharp specular reflections/refractions, very noisy direct illumination like dome lights, specular-specular sub-paths, sub surface scattering or hair, etc.