Disentangled Representation Learning in Real-World Image Datasets via Image Segmentation Prior

We propose a novel method that can learn easy-to-interpret latent representations in real-world image datasets using a VAE-based model by splitting an image into several disjoint regions. Our method performs object-wise disentanglement by exploiting image segmentation and alpha compositing. With rem...

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Bibliographic Details
Main Authors: Nao Nakagawa, Ren Togo, Takahiro Ogawa, Miki Haseyama
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9502079/