Posted on Monday, February 18 2019 @ 13:47 CET by Thomas De Maesschalck
In a new blog post, NVIDIA
explains what Deep Learning Super Sampling (DLSS) is and answers some criticisms about the technology. Among other things, Andrew Edelsten, Technical Director of Deep Learning at NVIDIA, promises the quality of DLSS will improve over time as NVIDIA adds more training data to the system:
Q: Some users mentioned blurry frames. Can you explain?
A: DLSS is a new technology and we are working hard to perfect it.
We built DLSS to leverage the Turing architecture’s Tensor Cores and to provide the largest benefit when GPU load is high. To this end, we concentrated on high resolutions during development (where GPU load is highest) with 4K (3840x2160) being the most common training target. Running at 4K is beneficial when it comes to image quality as the number of input pixels is high. Typically for 4K DLSS, we have around 3.5-5.5 million pixels from which to generate the final frame, while at 1920x1080 we only have around 1.0-1.5 million pixels. The less source data, the greater the challenge for DLSS to detect features in the input frame and predict the final frame.
We have seen the screenshots and are listening to the community’s feedback about DLSS at lower resolutions, and are focusing on it as a top priority. We are adding more training data and some new techniques to improve quality, and will continue to train the deep neural network so that it improves over time.
