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Monocular Neural Image Based Rendering with Continuous View Control: Difference between revisions
Monocular Neural Image Based Rendering with Continuous View Control (view source)
Revision as of 03:55, 14 June 2020
, 14 June 2020→Architecture
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The encoder converts images into latent points. | The encoder converts images into latent points. | ||
It consists of 8 convolutional blocks which each downsample the feature map. (Note that the | It consists of 8 convolutional blocks which each downsample the feature map. (Note that the supplementary material says 7 but their code actually uses 8). | ||
Each block is: Conv-BatchNorm-LeakyReLU. | Each block is: Conv-BatchNorm-LeakyReLU. | ||
The final output of the convolution blocks has size \((1, 1, 2**8)\). | |||
The output of the convolutional blocks are put through a fully connected layer and reshaped into a \(200 \times 3\) matrix. | The output of the convolutional blocks are put through a fully connected layer and reshaped into a \(200 \times 3\) matrix. | ||