I am a machine learning research engineer at Adobe Research in California, working on generative models for image generation and editing. I am interested in using generative models that allow conditional and unconditional generation and editing of images. I am also interested in few-shot learning 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.
For a full list, have a look at my Google Scholar page.
A neural architecture for automatically modifying an input high-resolution image according to a user's edits on its semantic segmentation map.
D. Liu, S. Shetty, T. Hinz, M. Fisher, R. Zhang, T. Park, E. Kalogerakis, ACM Transactions on Graphics (SIGGRAPH 2022) 2022.
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.
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.
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.
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.
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.