GFFE: G-buffer Free Frame Extrapolation for Low-latency Real-time Rendering
Songyin Wu, Deepak Vembar, Anton Sochenov, Selvakumar Panneer, Sungye, Kim, Anton Kaplanyan, Ling-Qi Yan

TL;DR
GFFE introduces a novel G-buffer free frame extrapolation method that generates future frames in real-time without additional latency, improving efficiency and ease of integration in high-resolution, high-frame-rate rendering.
Contribution
The paper presents a new G-buffer free extrapolation framework with a neural network that handles disocclusions and shading correction, enabling low-latency real-time rendering without G-buffer dependency.
Findings
Achieves comparable or better results than previous methods
More efficient performance and easier game integration
Handles disocclusions and shading correction effectively
Abstract
Real-time rendering has been embracing ever-demanding effects, such as ray tracing. However, rendering such effects in high resolution and high frame rate remains challenging. Frame extrapolation methods, which don't introduce additional latency as opposed to frame interpolation methods such as DLSS 3 and FSR 3, boost the frame rate by generating future frames based on previous frames. However, it is a more challenging task because of the lack of information in the disocclusion regions, and recent methods also have a high engine integration cost due to requiring G-buffers as input. We propose a \emph{G-buffer free} frame extrapolation, GFFE, with a novel heuristic framework and an efficient neural network, to plausibly generate new frames in real-time without introducing additional latency. We analyze the motion of dynamic fragments and different types of disocclusions, and design the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Vision and Imaging · Computer Graphics and Visualization Techniques · Advanced Image and Video Retrieval Techniques
