But while DLSS is designed to ingest an image and then generate a sharper version of the same image, the method from the Intelligent Systems Lab ingests an image and then enhances its photorealism by drawing from a dataset of real life imagery-specifically a dataset called Cityscapes which features street view imagery from the perspective of a car. In concept, the method is similar to NVIDIA’s Deep Learning Super Sampling (DLSS). The results are quite impressive, showing stability that far exceeds similar methods.

Researchers from Intel’s Intelligent Systems Lab have published research demonstrating a state of the art approach to creating truly photorealistic real-time graphics by layering a deep-learning system on top of GTA V’s existing rendering engine. While real-time raytracing takes us another step toward realistic graphics, there’s still a gap between even the best looking games today and true photorealism. Even so, it’s far from what would truly fit the definition of “photorealistic.”Īlthough we’ve been able to create pre-rendered truly photorealistic imagery for quite some time now, doing so in real-time is still a major challenge. While the technique in its research state is too slow for real gameplay today, it could represent a fundamentally new direction for real-time computer graphics of the future.ĭespite being released back in 2013, GTA V remains a pretty darn good looking game. Demonstrated with GTA V, the approach uses deep-learning to analyze frames generated by the game and then generate new frames from a dataset of real images. Researchers from Intel’s Intelligent Systems Lab have revealed a new method for enhancing computer-generated imagery with photorealistic graphics.

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