Future release roadmap

Innobright releases Altus on roughly a monthly schedule until Q1 2017. Below, you can see what features you’ll be seeing in the recent and upcoming point releases. Starting Q2, 2017, we plan to move to a quarterly release schedule.

 
 

Learning Based Filtering:

The most successful Monte Carlo denoising calculates the filter weights in a heuristic manner. Learning Based Filtering approaches this via the use of a neural network to automatically learn the complex relationship between the noisy scene and the ideal filter parameters, which is not possible via the heuristic rules. The automatic learning process will bring the next level of efficiency into the filtering of Monte Carlo images in a train and forget method such that the filter weights need not be calculated for each noisy image being filtered.


Real-time Denoising:

The holy grail of denoising is to be able to filter the noise of an image in real time. From a performance standpoint, this is the final step in filtering of noise in Monte Carlo rendering, o’course with the best possible quality. innoBright is working together with leading researchers in the field to crack this final frontier.