Low-Latency Space-Time Supersampling for Real-Time Rendering
Ruian He, Shili Zhou, Yuqi Sun, Ri Cheng, Weimin Tan, Bo Yan
Abstract
With the rise of real-time rendering and the evolution of display devices, there is a growing demand for post-processing methods that offer high-resolution content in a high frame rate. Existing techniques often suffer from quality and latency issues due to the disjointed treatment of frame supersampling and extrapolation. In this paper, we recognize the shared context and mechanisms between frame supersampling and extrapolation, and present a novel framework, Space-time Supersampling (STSS). By integrating them into a unified framework, STSS can improve the overall quality with lower latency. To implement an efficient architecture, we treat the aliasing and warping holes unified as reshading regions and put forth two key components to compensate the regions, namely Random Reshading Masking (RRM) and Efficient Reshading Module (ERM). Extensive experiments demonstrate that our approach achieves superior visual fidelity compared to state-of-the-art (SOTA) methods. Notably, the performance is achieved within only 4ms, saving up to 75% of time against the conventional two-stage pipeline that necessitates 17ms.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext edf96d09-ad3f-459f-a8da-e64c3b71ec51Cited by top-tier papers1
Ask how each one uses itBuilds on13
- Random Erasing Data AugmentationZhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li et al.AAAI 2020 · 4,134 citations
- Neural supersampling for real-time renderingLei Xiao, Salah Nouri, Matthew Chapman, Alexander Fix et al.SIGGRAPH 2020 · 114 citations
- RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-ResolutionZhicheng Geng, Luming Liang, Tianyu Ding, Ilya ZharkovCVPR 2022 · 103 citations
- Optimizing Video Prediction via Video Frame InterpolationYue Wu, Qiang Wen, Qifeng ChenCVPR 2022 · 47 citations
- Sparse Attention with Linear UnitsBiao Zhang, Ivan Titov, Rico SennrichEMNLP 2021 · 32 citations
Related papers
- Accelerating Stereo Rendering via Image Reprojection and Spatio-Temporal SupersamplingSipeng Yang, Junhao Zhuge, Jiayu Ji, Qingchuan Zhu et al.IEEE VR 2025 · 3 citations
- Mob-FGSR: Frame Generation and Super Resolution for Mobile Real-Time RenderingSipeng Yang, Qingchuan Zhu, Junhao Zhuge, Qiang Qiu et al.SIGGRAPH 2024 · 17 citations
- Neural Super-Resolution for Real-Time Rendering with Radiance DemodulationJia Li, Ziling Chen, Xiaolong Wu, Lu Wang et al.CVPR 2024
- Space-Time-Aware Multi-Resolution Video EnhancementMuhammad Haris, Greg Shakhnarovich, Norimichi UkitaCVPR 2020
- Hardware-Rasterized Ray-Based Gaussian SplattingSamuel Rota Bulò, Nemanja Bartolovic, Lorenzo Porzi, Peter KontschiederCVPR 2025
