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Biography

Florian Strohm is a PhD student in the Perceptual User Interfaces group since January 2020. He holds a Bachelor's and Master’s degree in Computer Science from the University of Stuttgart. During his Master’s studies he focused on the fields of Computer Vision and Machine Learning, and he won the Rul Gunzenhäuser Prize for his master thesis. His research interests are analyzing cognitive processes such as how humans encode visual stimuli in memory and the synthetic reconstruction of such stimuli.


Teaching

2022
Machine Perception and Learning (Tutor) (summer)Master
 
Machine Perception and Learning (Tutor) (winter)Master
2021
Mensch-Computer-Interaktion (Teaching Assistant)Bachelor
 
Machine Learning and Computer Vision for HCI (Fachpraktikum)Master
2020
Machine Learning and Computer Vision for HCI (Fachpraktikum)Master
 
Mensch-Computer-Interaktion (Teaching Assistant)Bachelor
2018
Information Retrieval and Text Mining (Teaching Assistant)Bachelor/Master
2017
Rechnerorganisation (Tutor)Bachelor

Supervision

2023
Web Interface for Interactive Face Reconstruction (B.Sc.) Lewin Fritzenschaft
 
Disentangled Face Embeddings (B.Sc.) Michael Linder
2022
Video-based Representation Learning for Emotion Recognition (M.Sc.) Shangrui Nie**
 
Interpreting Neural Attention in NLP with Human Visual Attention (M.Sc. Research Project) Shangrui Nie**
 
Conditional GAN-based Mask Guided Portrait Editing (M.Sc. Research Project) Prabhakar Panday
 
Augmenting fMRI-based Image Reconstruction with Image Labelling (M.Sc.) Jamie Ullerich
 
Intention Recognition via Eye Gaze for Hierarchical Imitation Learning (M.Sc.) Anna Penzkofer
 
Fine-Grained Facial Composite Generation using Facial Landmarks (B.Sc.) Markus Kaltenecker
2021
Image Reconstruction from Human Brain Activity by Variational Autoencoder and Adversarial Learning (M.Sc.) Mariia Podguzova**
 
Analysing the Influence of Facial Feature Alteration on Person Identification (B.Sc.) Britta Schulz
*Co-supervised with Ekta Sood

Open Thesis Projects

 
Mental Face Reconstruction by Interactive MorphingMaster
 
User Embedding from RankingBachelor/Master
 
Fixation Importance PredictionMaster

Publications

  1. Learning User Embeddings from Human Gaze for Personalised Saliency Prediction

    Learning User Embeddings from Human Gaze for Personalised Saliency Prediction

    Florian Strohm, Mihai Bâce, Andreas Bulling

    Proc. ACM on Human-Computer Interaction (PACM HCI), pp. , 2024.

    Abstract Links BibTeX Project

  1. SeFFeC: Semantic Facial Feature Control for Fine-grained Face Editing

    SeFFeC: Semantic Facial Feature Control for Fine-grained Face Editing

    Florian Strohm, Mihai Bâce, Markus Kaltenecker, Andreas Bulling

    arXiv:2403.13972, pp. 1–18, 2024.

    Abstract Links BibTeX Project

  1. Usable and Fast Interactive Mental Face Reconstruction

    Usable and Fast Interactive Mental Face Reconstruction

    Florian Strohm, Mihai Bâce, Andreas Bulling

    Proc. ACM Symposium on User Interface Software and Technology (UIST), pp. 1–15, 2023.

    Abstract Links BibTeX Project

  2. Int-HRL: Towards Intention-based Hierarchical Reinforcement Learning

    Int-HRL: Towards Intention-based Hierarchical Reinforcement Learning

    Anna Penzkofer, Simon Schaefer, Florian Strohm, Mihai Bâce, Stefan Leutenegger, Andreas Bulling

    Proc. Adaptive and Learning Agents Workshop (ALA), pp. 1–7, 2023.

    Abstract Links BibTeX Project

  3. Facial Composite Generation with Iterative Human Feedback

    Facial Composite Generation with Iterative Human Feedback

    Florian Strohm, Ekta Sood, Dominike Thomas, Mihai Bâce, Andreas Bulling

    Proc. The 1st Gaze Meets ML workshop, PMLR, pp. 165–183, 2023.

    Abstract Links BibTeX Project

  1. Neural Photofit: Gaze-based Mental Image Reconstruction

    Neural Photofit: Gaze-based Mental Image Reconstruction

    Florian Strohm, Ekta Sood, Sven Mayer, Philipp Müller, Mihai Bâce, Andreas Bulling

    Proc. IEEE International Conference on Computer Vision (ICCV), pp. 245-254, 2021.

    Abstract Links BibTeX Project

  2. VQA-MHUG: A gaze dataset to study multimodal neural attention in VQA

    VQA-MHUG: A gaze dataset to study multimodal neural attention in VQA

    Ekta Sood, Fabian Kögel, Florian Strohm, Prajit Dhar, Andreas Bulling

    Proc. ACL SIGNLL Conference on Computational Natural Language Learning (CoNLL), pp. 27–43, 2021.

    Abstract Links BibTeX Project Oral presentation

  1. An Empirical Analysis of the Role of Amplifiers, Downtoners, and Negations in Emotion Classification in Microblogs

    An Empirical Analysis of the Role of Amplifiers, Downtoners, and Negations in Emotion Classification in Microblogs

    Florian Strohm, Roman Klinger

    IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA), pp. 673-681, 2018.

    Abstract Links BibTeX Project