Q: In this task, you are given the abstract of a research paper. Your task is to generate a summary of this abstract. Your summary should not be very short, but it's better if it's not more than 30 words.
We present and discuss a simple image preprocessing method for learning disentangled latent factors.
In particular, we utilize the implicit inductive bias contained in features from networks pretrained on the ImageNet database.
We enhance this bias by explicitly fine-tuning such pretrained networks on tasks useful for the NeurIPS2019 disentanglement challenge, such as angle and position estimation or color classification.
Furthermore, we train a VAE on regionally aggregate feature maps, and discuss its disentanglement performance using metrics proposed in recent literature.
A:
We use supervised finetuning of feature vectors to improve transfer from simulation to the real world