Preprints and Submissions⌗

  • Skenderi, G., Capogrosso, L., Toaiari, A., Denitto, M., Fummi, F., Melzi, S., & Cristani, M. (2023). Disentangled Latent Spaces Facilitate Data-Driven Auxiliary Learning. arXiv:2310.09278. (Under review in Elsevier Pattern Recognition Letters).

  • Skenderi, G., Li, H., Tang, J., & Cristani, M. (2023). Graph-level Representation Learning with Joint-Embedding Predictive Architectures. arXiv:2309.16014.

Conference papers⌗

  • Turetta, C., Skenderi, G., Capogrosso, L., Demrozi, F., Kindt, P. H., Masrur, A., … & Pravadelli, G. (2023, April). Towards Deep Learning-based Occupancy Detection Via WiFi Sensing in Unconstrained Environments. In 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) (pp. 1-6). IEEE.

  • Skenderi, G., Joppi, C., Denitto, M., & Cristani, M. (2022). On the use of learning-based forecasting methods for ameliorating fashion business processes: A position paper. 2nd International Workshop on Industrial Machine Learning @ ICPR22.

  • Capogrosso, L., Skenderi, G., Girella, F., Fummi, F., & Cristani, M. (2022). Toward smart doors: A position paper. 2nd International Workshop on Industrial Machine Learning @ ICPR22.

  • Sampieri, A., di Melendugno, G.M.D.A., Avogaro, A., Cunico, F., Setti, F., Skenderi, G., Cristani, M. and Galasso, F., (2022, October). Pose forecasting in industrial human-robot collaboration. In European Conference on Computer Vision (pp. 51-69). Cham: Springer Nature Switzerland.

  • Joppi, C.*, Skenderi, G.*, & Cristani, M. (2022, October). POP: Mining POtential Performance of new fashion products via webly cross-modal query expansion. In European Conference on Computer Vision (pp. 34-50). Cham: Springer Nature Switzerland.

  • Skenderi, G., Joppi, C., Denitto, M., Scarpa, B., & Cristani, M. (2022). The multi-modal universe of fast-fashion: the Visuelle 2.0 benchmark. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 2241-2246).

  • Giuliari, F., Skenderi, G., Cristani, M., Wang, Y., & Del Bue, A. (2022). Spatial commonsense graph for object localisation in partial scenes. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 19518-19527).

  • Godi, M.*, Joppi, C.*, Skenderi, G.*, & Cristani, M. (2022). MovingFashion: a Benchmark for the Video-to-Shop Challenge. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 1678-1686).

  • Skenderi, G., Bozzini, A., Capogrosso, L., Agrillo, E. C., Perbellini, G., Fummi, F., & Cristani, M. (2021, September). Dohmo: Embedded computer vision in co-housing scenarios. In 2021 Forum on specification & Design Languages (FDL) (pp. 01-08). IEEE.

Journal papers⌗

  • Skenderi, G., Joppi, C., Denitto, M., & Cristani, M. (2024). Well googled is half done: Multimodal forecasting of new fashion product sales with image-based google trends. Journal of Forecasting, 1–16. https://doi.org/10.1002/for.3104

  • Giuliari, F., Skenderi, G., Cristani, M., Del Bue, A., & Wang, Y. (2023). Leveraging commonsense for object localisation in partial scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence.