PhD Candidate

      University of Hamburg

    I am a machine learning reseach engineer at Adobe Research and a 4th-year PhD student at the Knowledge Technology group at the University of Hamburg. I work on generative models that learn visual representation in a semi- or unsupervised way. This includes applications such as unconditional image generation, text-to-image synthesis, and disentangled representations. I am also interested in few-shot learning with and the automatic evaluation of generative models.

    I completed my Bachelor degree in Business Informatics at the University of Mannheim, during which I also studied at the National University of Singapore for one semester. Following that, I did a research oriented Master degree in Intelligent Adaptive Systems at the University of Hamburg.


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Selected Publications

For a full list, have a look at my Google Scholar page.

      Improved Techniques for Training Single-Image GANs

      Improving the results and training speed of single-image GANs.

      T. Hinz, M. Fisher, O. Wang, S. Wermter, IEEE Winter Conference on Applications of Computer Vision 2021.

      Semantic Object Accuracy for Generative Text-to-Image Synthesis

      A novel GAN architecture and an improved metric to evaluate generative text-to-image synthesis models.

      T. Hinz, S. Heinrich, S. Wermter, IEEE Transactions on Pattern Analysis and Machine Intelligence 2020.

      Generating Multiple Objects at Spatially Distinct Locations

      Fine-grained control over the placement and identity of objects in images generated with a Generative Adversarial Network.

      T. Hinz, S. Heinrich, S. Wermter, International Conference on Learning Representations 2019.

      Image Generation and Translation with Disentangled Representations

      Controllable image generation and translation with very little supervision.

      T. Hinz, S. Wermter, IEEE International Joint Conference on Neural Networks 2018.

      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.

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Curriculum Vitae