Video Frame Synthesis Using Deep Voxel Flow
Chinese University of Hong Kong · University of Illinois Urbana-Champaign · +1 more institution
Abstract
We address the problem of synthesizing new video frames in an existing video, either in-between existing frames (interpolation), or subsequent to them (extrapolation). This problem is challenging because video appearance and motion can be highly complex. Traditional optical-flow-based solutions often fail where flow estimation is challenging, while newer neural-network-based methods that hallucinate pixel values directly often produce blurry results. We combine the advantages of these two methods by training a deep network that learns to synthesize video frames by flowing pixel values from existing ones, which we call deep voxel flow. Our method requires no human supervision, and any video can be used as…
Citation impact
- FWCI
- 29.48
- Percentile
- 100%
- References
- 61
Authors
5Topics & keywords
- Hallucinating
- Computer science
- Artificial intelligence
- Computer vision
- Optical flow
- Interpolation (computer graphics)
- Extrapolation
- Frame (networking)