TOBIAS HINZ
Machine Learning
Research Engineer
Adobe Research
I am a machine learning reseach engineer at Adobe Research working on GANs for image generation and editing. I am interested in using generative models to learn image representations that allow for both editing and faithful reconstruction of the original input, e.g. faces or bodies. Other reseach interests of mine include unconditional image generation, text-to-image synthesis, and compositional representations for complex scenes. I am also interested in few-shot learning with GANs and the automatic evaluation of generative models.
I obtained my PhD at the Knowledge Technology group at the University of Hamburg (Germany). Before that, I completed a research oriented Master's degree in Intelligent Adaptive Systems at the University of Hamburg. I received a Bachelor's degree in Business Informatics at the University of Mannheim, during which I also studied at the National University of Singapore for one semester.
News
- 04/2021: I successfully defended my PhD thesis.
- 02/2021: Have a look at our paper on Few-Shot Character Animation (code available).
- 01/2021: Check out our latest review paper on Adversarial Text-to-Image Synthesis.
- 01/2021: I started a new position as machine learning research engineer with Adobe Research.
- 11/2020: Our work on Single-Image GANs (code available) got accepted to WACV 2021.
- 09/2020: Some thoughts on my summer internship at Adobe Research.
- 09/2020: Our work on evaluating GANs got accepted to TPAMI.
- 06/2020: I started my research internship with Adobe. Big thanks to Adobe for facilitating internships via home-office.
- 03/2020: We posted our work on Single-Image GANs with the available code and blog post.
- 01/2020: I will join Matthew Fisher and Oliver Wang at Adobe in San Francisco this summer for a research internship.
My Remote Internship with Adobe Research (Summer 2020)
Posted on 18 Sep 2020 | Reading time: 3 minutes
I had the chance to do an internship with Adobe Research in San-Francisco. Due to COVID all Adobe staff are working from home and so I did my internship remotely from Germany.
Improved Techniques for Training Single-Image GANs
Posted on 24 Mar 2020 | Reading time: 7 minutes
Overview of our paper about training GANs on a single image for tasks such as image generation, image harmonization, and image animation.
Semantic Object Accuracy for Generative Text-to-Image Synthesis
Posted on 30 Oct 2019 | Reading time: 8 minutes
Overview of our paper about our new model and evaluation metric for generative text-to-image synthesis models.
My Time At The Deep Learning And Reinforcement Learning Summer School (DLRLSS) in Edmonton (Canada)
Posted on 06 Aug 2019 | Reading time: 17 minutes
After attending the EEMLSS I was lucky enough to also attend the Deep Learning And Reinforcement Learning Summer School (DLRLSS) in Edmonton (Canada) 2019.
See All
Selected Publications
For a full list, have a look at my Google Scholar page.
Speeding Up the Hyperparameter Optimization Of Deep Convolutional Neural Networks
How to use lower dimensional data representations to speed up the hyperparameter optimization for CNNs processing images..
T. Hinz, N. Navarro-Guerrero, S. Magg, S. Wermter, International Journal of Computational Intelligence and Applications 2018.
See All