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

Roman Shapovalov, Yanir Kleiman, Ignacio Rocco, David Novotný, A. Vedaldi +4 more
7/1/2023

No official code found. Best implementation: facebookresearch/replay_dataset (39 stars, last commit 2023-06-23).

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 view-points 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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Code Implementations(1)

Download scripts and tools for Replay dataset.

391PythonJun 23, 20233 years agoNOASSERTION

Cite this paper

@article{shapovalov2023replay,
  title  = {Replay: Multi-modal Multi-view Acted Videos for Casual Holography},
  author = {Roman Shapovalov and Yanir Kleiman and Ignacio Rocco and David Novotný and A. Vedaldi and Changan Chen and Filippos Kokkinos and Benjamin Graham and N. Neverova},
  year   = {2023},
  eprint = {2307.12067},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2307.12067},
  journal = {ICCV 2023 2023}
}

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