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This report to our stage 1 submission to the NeurIPS 2019 disentanglementchallenge presents a simple image preprocessing method for training VAEsleading to improved disentanglement compared to directly using the images. Inparticular, we propose to use regionally aggregated feature maps extracted fromCNNs pretrained on ImageNet. Our method achieved the 2nd place in stage 1 ofthe challenge. Code is available athttps://github.com/mseitzer/neurips2019-disentanglement-challenge.

NeurIPS 2019 Disentanglement Challenge: Improved Disentanglement through Aggregated Convolutional Feature Maps