Replay: Multi-modal Multi-view Acted Videos for Casual Holography

Roman Shapovalov; Yanir Kleiman; Ignacio Rocco; David Novotny; Andrea Vedaldi; Changan Chen; Filippos Kokkinos; Ben Graham; Natalia Neverova

arXiv · 2307.12067

Replay: Multi-modal Multi-view Acted Videos for Casual Holography

Roman Shapovalov·Yanir Kleiman·Ignacio Rocco·David Novotny·Andrea Vedaldi·Changan Chen·Filippos Kokkinos·Ben Graham·Natalia Neverova

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Abstract

We introduce Replay, a collection of multi-view, multi-modal videos of humans interacting socially. Each scene is filmed in high production quality, from different viewpoints with several static cameras, as well as wearable action cameras, and recorded with a large array of microphones at different positions in the room. Overall, the dataset contains over 4000 minutes of footage and over 7 million timestamped high-resolution frames annotated with camera poses and partially with foreground masks. The Replay dataset has many potential applications, such as novel-view synthesis, 3D reconstruction, novel-view acoustic synthesis, human body and face analysis, and training generative models. We provide a benchmark for training and evaluating novel-view synthesis, with two scenarios of different difficulty. Finally, we evaluate several baseline state-of-the-art methods on the new benchmark.

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Roman Shapovalov, Yanir Kleiman, Ignacio Rocco, David Novotny, Andrea Vedaldi, Changan Chen, Filippos Kokkinos, Ben Graham, Natalia Neverova. 2023-07-22. Replay: Multi-modal Multi-view Acted Videos for Casual Holography. https://arxiv.org/abs/2307.12067

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