HyperReel: High-Fidelity 6-DoF Video with Ray-Conditioned Sampling

被引:26
|
作者
Attal, Benjamin [1 ,4 ]
Huang, Jia-Bin [2 ,4 ]
Richardt, Christian [3 ]
Zollhofer, Michael [3 ]
Kopf, Johannes [4 ]
O'Toole, Matthew [1 ]
Kim, Changil [4 ]
机构
[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
[2] Univ Maryland, College Pk, MD USA
[3] Real Labs Res, Pittsburgh, PA USA
[4] Meta, Cambridge, MA USA
关键词
FIELDS;
D O I
10.1109/CVPR52729.2023.01594
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Volumetric scene representations enable photorealistic view synthesis for static scenes and form the basis of several existing 6-DoF video techniques. However, the volume rendering procedures that drive these representations necessitate careful trade-offs in terms of quality, rendering speed, and memory efficiency. In particular, existing methods fail to simultaneously achieve real-time performance, small memory footprint, and high-quality rendering for challenging real-world scenes. To address these issues, we present HyperReel - a novel 6-DoF video representation. The two core components of HyperReel are: (1) a ray-conditioned sample prediction network that enables high-fidelity, high frame rate rendering at high resolutions and (2) a compact and memory-efficient dynamic volume representation. Our 6-DoF video pipeline achieves the best performance compared to prior and contemporary approaches in terms of visual quality with small memory requirements, while also rendering at up to 18 frames-per-second at megapixel resolution without any custom CUDA code.
引用
收藏
页码:16610 / 16620
页数:11
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