Matthias Springstein

Publications by categories in reversed chronological order. Generated by jekyll-scholar.

Number of publications: 22

Conference Articles

2024

  1. [1]
    E. Müller-Budack, M. Springstein, M. Plank, J. Sittel, R. Mauer, O. Bulgakowa, M. Burghardt, J. A. Bateman, and R. Ewerth:
    TIB AV-Analytics: A Computational Tool for Film and Video Analysis
    In: Conference of the Society for Cognitive Studies of the Moving Image, SCSMI 2024, Budapest, Hungary, June 5-8, 2024, 2024.
  2. [2]
    M. Springstein, S. Schneider, J. Rahnama, J. Stalter, M. Kristen, E. Müller-Budack, and R. Ewerth:
    Visual Narratives: Large-scale Hierarchical Classification of Art-historical Images
    In: IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2024, Waikoloa, HI, USA, January 3-8, 2024, pp. 7195–7205. IEEE, 2024.
    https://doi.org/10.1109/WACV57701.2024.00705
  3. [3]
    G. Tahmasebzadeh, M. Springstein, R. Ewerth, and E. Müller-Budack:
    Few-Shot Event Classification in Images using Knowledge Graphs for Prompting
    In: IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2024, Waikoloa, HI, USA, January 3-8, 2024, pp. 7271–7280. IEEE, 2024.
    https://doi.org/10.1109/WACV57701.2024.00712

2023

  1. [1]
    M. Springstein, M. Stamatakis, M. Plank, J. Sittel, R. Mauer, O. Bulgakowa, R. Ewerth, and E. Müller-Budack:
    TIB AV-Analytics: A Web-based Platform for Scholarly Video Analysis and Film Studies
    In: ACM Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, July 23-27, 2023, pp. 3195–3199. ACM, 2023.
    https://doi.org/10.1145/3539618.3591820
  2. [2]
    J. Theiner, N. Nommensen, J. Rhotert, M. Springstein, E. Müller-Budack, and R. Ewerth:
    Analyzing Results of Depth Estimation Models With Monocular Criteria
    In: Explainable AI for Computer Vision Workshop co-located with the IEEE/CFV Conference on Computer Vision and Pattern Recognition, XAI4CV@CVPR 2023, Vancouver, Canada, June 19, pp. 3738-3742. IEEE/CVF, 2023.
    https://openaccess.thecvf.com/content/CVPR2023W/XAI4CV/html/Theiner_Analyzing_Results_of_Depth_Estimation_Models_With_Monocular_Criteria_CVPRW_2023_paper.html

2022

  1. [1]
    M. Springstein, S. Schneider, C. Althaus, and R. Ewerth:
    Semi-supervised Human Pose Estimation in Art-historical Images
    In: ACM Conference on Multimedia, MM 2022, Lisboa, Portugal, October 10 - 14, 2022, pp. 1107–1116. ACM, 2022.
    https://doi.org/10.1145/3503161.3548371
  2. [2]
    S. Schneider, M. Springstein, J. Rahnama, H. Kohle, R. Ewerth, and E. Hüllermeier:
    iART - Eine Suchmaschine zur Unterstützung von bildorientierten Forschungsprozessen
    In: Tagung des Verbands Digital Humanities im deutschsprachigen Raum, DHd 2022, Potsdam, Germany, March 7 - 11, 2022, 2022.
    https://doi.org/10.5281/ZENODO.6310.528175

2021

  1. [1]
    E. Müller-Budack, M. Springstein, S. Hakimov, K. Mrutzek, and R. Ewerth:
    Ontology-driven Event Type Classification in Images
    In: IEEE Winter Conference on Applications of Computer Vision, WACV 2021, Virtual Event, January 3-8, 2021, pp. 2927–2937. IEEE, 2021.
    https://doi.org/10.1109/WACV48630.2021.00297
  2. [2]
    M. Springstein, S. Schneider, J. Rahnama, E. Hüllermeier, H. Kohle, and R. Ewerth:
    iART: A Search Engine for Art-Historical Images to Support Research in the Humanities
    In: ACM Conference on Multimedia, MM 2021, Virtual Event, China, October 20 - 24, 2021, pp. 2801–2803. ACM, 2021.
    https://doi.org/10.1145/3474085.3478564
  3. [3]
    M. Springstein, E. Müller-Budack, and R. Ewerth:
    Unsupervised Training Data Generation of Handwritten Formulas using Generative Adversarial Networks with Self-Attention
    In: Workshop on Multi-Modal Pre-Training for Multimedia Understanding co-located with the International Conference on Multimedia Retrieval, MMPT@ICMR 2021, Virtual Event, August 21, 2021, pp. 46–54. ACM, 2021.
    https://doi.org/10.1145/3463945.3469059
  4. [4]
    M. Springstein, E. Müller-Budack, and R. Ewerth:
    QuTI! Quantifying Text-Image Consistency in Multimodal Documents
    In: ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2021, Virtual Event, July 11-15, 2021, pp. 2575–2579. ACM, 2021.
    https://doi.org/10.1145/3404835.3462796

2020

  1. [1]
    S. Schneider, M. Springstein, J. Rahnama, E. Hüllermeier, R. Ewerth, and H. Kohle:
    The Dissimilar in the Similar. An Attribute-guided Approach to the Subject-specific Classification of Art-historical Objects
    In: Jahrestagung der Gesellschaft für Informatik, INFORMATIK 2020, Karlsruhe, Germany, September 28 - October 2, 2020, P-307, pp. 1355–1364. GI, 2020.
    https://doi.org/10.18420/INF2020_127

2019

  1. [1]
    C. Otto, M. Springstein, A. Anand, and R. Ewerth:
    Understanding, Categorizing and Predicting Semantic Image-Text Relations
    In: International Conference on Multimedia Retrieval, ICMR 2019, Ottawa, ON, Canada, June 10-13, 2019, pp. 168–176. ACM, 2019.
    Best Paper Award
    https://doi.org/10.1145/3323873.3325049

2018

  1. [1]
    M. Springstein, H. H. Nguyen, A. Hoppe, and R. Ewerth:
    TIB-arXiv: An Alternative Search Portal for the arXiv Pre-print Server
    In: International Conference on Theory and Practice of Digital Libraries, TPDL 2018, Porto, Portugal, September 10-13, 2018, pp. 295–298. Springer, 2018.
    https://doi.org/10.1007/978-3-030-00066-0_26
  2. [2]
    M. Springstein, H. H. Nguyen, A. Hoppe, and R. Ewerth:
    TIB-arXiv: An Alternative Search Portal for the arXiv Pre-print Server
    In: International Conference on Theory and Practice of Digital Libraries, TPDL 2018, Porto, Portugal, September 10-13, 2018, 11057, pp. 295–298. Springer, 2018.
    https://doi.org/10.1007/978-3-030-00066-0_26

2017

  1. [1]
    R. Ewerth, M. Springstein, E. Müller, A. Balz, J. Gehlhaar, T. Naziyok, K. Dembczynski, and E. Hüllermeier:
    Estimating relative depth in single images via rankboost
    In: IEEE International Conference on Multimedia and Expo, ICME 2017, Hong Kong, China, July 10-14, 2017, pp. 919–924. IEEE Computer Society, 2017.
    https://doi.org/10.1109/ICME.2017.8019434
  2. [2]
    R. Ewerth, M. Springstein, L. A. Phan-Vogtmann, and J. Schütze:
    "Are Machines Better Than Humans in Image Tagging?" - A User Study Adds to the Puzzle
    In: European Conference on Information Retrieval, ECIR 2017, Aberdeen, UK, April 8-13, 2017, 10193, pp. 186–198, 2017.
    https://doi.org/10.1007/978-3-319-56608-5_15
  3. [3]
    E. Müller, M. Springstein, and R. Ewerth:
    "When Was This Picture Taken?" - Image Date Estimation in the Wild
    In: European Conference on Information Retrieval, ECIR 2017, Aberdeen, UK, April 8-13, 2017, pp. 619–625, 2017.
    https://doi.org/10.1007/978-3-319-56608-5_57

2016

  1. [1]
    M. Springstein and R. Ewerth:
    On the Effects of Spam Filtering and Incremental Learning for Web-Supervised Visual Concept Classification
    In: ACM International Conference on Multimedia Retrieval, ICMR 2016, New York, New York, USA, June 6-9, 2016, pp. 377–380. ACM, 2016.
    https://doi.org/10.1145/2911996.2912072

inbook

2021

  1. [1]
    E. Müller-Budack, K. Pustu-Iren, S. Diering, M. Springstein, and R. Ewerth:
    Image Analytics in Web Archives
    The Past Web: Exploring Web Archives, pp. 141–151. Springer International Publishing, 2021.
    https://doi.org/10.1007/978-3-030-63291-5_11

Journal Articles

2020

  1. [1]
    C. Otto, M. Springstein, A. Anand, and R. Ewerth:
    Characterization and Classification of Semantic Image-Text Relations
    International Journal of Multimedia Information Retrieval, 9(1), pp. 31–45, 2020.
    Invited Paper (Best Papers of ACM ICMR 2019)
    https://doi.org/10.1007/s13735-019-00187-6

2017

  1. [1]
    M. Mühling, N. Korfhage, E. Müller, C. Otto, M. Springstein, T. Langelage, U. Veith, R. Ewerth, and B. Freisleben:
    Deep learning for content-based video retrieval in film and television production
    Multimedia Tools and Applications, 76(21), pp. 22169–22194, 2017.
    https://doi.org/10.1007/s11042-017-4962-9