Recently, learning methods have been designed to create Multiplane Images (MPIs) for view synthesis. While MPIs are extremely powerful and facilitate high quality renderings, a great amount of memory is required, making them impractical for many applications. In this paper, we propose a learning method that optimizes the available memory to render compact and adaptive MPIs. Our MPIs avoids redundant information and takes into account the scene geometry to determine the depth sampling.
Compact and Adaptive Multiplane Images for View Synthesis
Compact and Adaptive Multiplane Images for View Synthesis
Compact and Adaptive Multiplane Images for View Synthesis
Research Paper / Sep 2021 / Video coding, Machine learning/ Deep learning /Artificial Intelligence, Image processing, Computer Graphics
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