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Abstract
Modeling and rendering of dynamic scenes is challenging, as natural scenes often contain complex phenomena such as thin structures, evolving topology, translucency, scattering, occlusion, and biological motion. Mesh-based reconstruction and tracking often fail in these cases, and other approaches (e.g., light field video) typically rely on constrained viewing conditions, which limit interactivity. We circumvent these difficulties by presenting a learning-based approach to representing dynamic objects inspired by the integral projection model used in tomographic imaging. The approach is supervised directly from 2D images in a multi-view capture setting and does not require explicit reconstruction or tracking of…
Citation impact
654
total citations
- FWCI
- 26.43
- Percentile
- 100%
- References
- 70
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Authors
6Topics & keywords
Topics
Keywords
- Computer science
- Rendering (computer graphics)
- Artificial intelligence
- Computer vision
- Grid
- Computer graphics (images)
- Mathematics
UN Sustainable Development Goals
- Sustainable cities and communities
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