ICML 2020

Timezone: »

Poster

Semi-Supervised StyleGAN for Disentanglement Learning

Weili Nie · Tero Karras · Animesh Garg · Shoubhik Debnath · Anjul Patney · Ankit Patel · Anima Anandkumar

Thu Jul 16 07:00 AM -- 07:45 AM & Thu Jul 16 08:00 PM -- 08:45 PM (PDT) @

in Poster Session 42 »

Disentanglement learning is crucial for obtaining disentangled representations and controllable generation. Current disentanglement methods face several inherent limitations: difficulty with high-resolution images, primarily focusing on learning disentangled representations, and non-identifiability due to the unsupervised setting. To alleviate these limitations, we design new architectures and loss functions based on StyleGAN (Karras et al., 2019), for semi-supervised high-resolution disentanglement learning. We create two complex high-resolution synthetic datasets for systematic testing. We investigate the impact of limited supervision and find that using only 0.25%~2.5% of labeled data is sufficient for good disentanglement on both synthetic and real datasets. We propose new metrics to quantify generator controllability, and observe there may exist a crucial trade-off between disentangled representation learning and controllable generation. We also consider semantic fine-grained image editing to achieve better generalization to unseen images.

Keywords: Deep Generative Models · Generative Adversarial Networks · Representation Learning · Semi-supervised learning · Deep Learning - Generative Models and Autoencoders

Author Information

Weili Nie (Rice University)

Tero Karras (NVIDIA)

Animesh Garg (University of Toronto, Vector Institute, Nvidia)

Shoubhik Debnath (Nvidia)

Anjul Patney (Nvidia)

Ankit Patel (Rice University, Baylor College of Medicine)

Anima Anandkumar (Amazon AI & Caltech)

Anima Anandkumar is a Bren Professor at Caltech and Director of ML Research at NVIDIA. She was previously a Principal Scientist at Amazon Web Services. She is passionate about designing principled AI algorithms and applying them to interdisciplinary domains. She has received several honors such as the IEEE fellowship, Alfred. P. Sloan Fellowship, NSF Career Award, Young investigator awards from DoD, Venturebeat’s “women in AI” award, NYTimes GoodTech award, and Faculty Fellowships from Microsoft, Google, Facebook, and Adobe. She is part of the World Economic Forum's Expert Network. She has appeared in the PBS Frontline documentary on the “Amazon empire” and has given keynotes in many forums such as the TEDx, KDD, ICLR, and ACM. Anima received her BTech from Indian Institute of Technology Madras, her PhD from Cornell University, and did her postdoctoral research at MIT and assistant professorship at University of California Irvine.