HyperReel: High-Fidelity 6-DoF Video with Ray-Conditioned Sampling
HyperReel is a novel 6-DoF video representation that is unique compared to other approaches in that it both accelerates volume rendering and improves rendering quality, especially for challenging view dependent scenes. Find out more about it!
Abstract
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.
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Founder and Chief Editor of Data Phoenix — a San Francisco Bay Area media and education platform focused on AI and Data.
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