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@inproceedings{SSBC25,

title = {Privacy-enhancing Sclera Segmentation Benchmarking Competition: SSBC 2025},

author = {Vitek, Matej and Tomašević, Darian and Das, Abhijit and Nathan, Sabari and Özbulak, Gökhan and Tataroğlu Özbulak and Gözde Ayşe and Calbimonte, Jean-Paul and Anjos, André and Bhatt, Hariohm Hemant and Premani, Dhruv Dhirendra and Chaudhari, Jay and Wang, Caiyong and Jiang, Jian and Zhang, Chi and Zhang, Qi and Ganapathi, Iyyakutti Iyappan and Ali, Syed Sadaf and Velayudan, Divya and Assefa, Maregu and Werghi, Naoufel and Daniels, Zachary A. and John, Leeon and Vyas, Ritesh and Khiarak, Jalil Nourmohammadi and Saeed, Taher Akbari and Nasehi, Mahsa and Kianfar, Ali and Pashazadeh Panahi, Mobina and Sharma, Geetanjali and Panth, Pushp Raj and Ramachandra, Raghavendra and Nigam, Aditya and Pal, Umapada and Peer, Peter and Štruc, Vitomir},

url = {https://lmi.fe.uni-lj.si/wp-content/uploads/2025/08/IJCB_SSBC_25.pdf},

year  = {2025},

date = {2025-09-08},

booktitle = {Proceedings of the IEEE International Joint Conference on Biometrics (IJCB 2025)},

pages = {1--13},

publisher = {IEEE},

keywords = {biometrics, deep learning, sclera segmentation, segmentation, SSBC},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{SSBC2020,

title = {SSBC 2020: Sclera Segmentation Benchmarking Competition in the Mobile Environment},

author = {M. Vitek and A. Das and Y. Pourcenoux and A. Missler and C. Paumier and S. Das and I. De Ghosh and D. R. Lucio and L. A. Zanlorensi Jr. and D. Menotti and F. Boutros and N. Damer and J. H. Grebe and A. Kuijper and J. Hu and Y. He and C. Wang and H. Liu and Y. Wang and Z. Sun and D. Osorio-Roig and C. Rathgeb and C. Busch and J. Tapia and A.~Valenzuela and G. Zampoukis and L. Tsochatzidis and I. Pratikakis and S. Nathan and R. Suganya and V. Mehta and A. Dhall and K. Raja and G. Gupta and J. N. Khiarak and M. Akbari-Shahper and F. Jaryani and M. Asgari-Chenaghlu and R. Vyas and S. Dakshit and S. Dakshit and P. Peer and U. Pal and V. Štruc},

url = {https://lmi.fe.uni-lj.si/wp-content/uploads/2020/11/IJCB_SSBC_2020.pdf},

year  = {2020},

date = {2020-09-28},

booktitle = {International Joint Conference on Biometrics (IJCB 2020)},

pages = {1--10},

abstract = {The paper presents a summary of the 2020 Sclera Segmentation Benchmarking Competition (SSBC), the 7th in the series of group benchmarking efforts centred around the problem of sclera segmentation. Different from previous editions, the goal of SSBC 2020 was to evaluate the performance of sclera-segmentation models on images captured with mobile devices. The competition was used as a platform to assess the sensitivity of existing models to i) differences in mobile devices used for image capture and ii) changes in the ambient acquisition conditions. 26 research groups registered for SSBC 2020, out of which 13 took part in the final round and submitted a total of 16 segmentation models for scoring. These included a wide variety of deep-learning solutions as well as one approach based on standard image processing techniques. Experiments were conducted with three recent datasets. Most of the segmentation models achieved relatively consistent  performance across images captured with different mobile devices (with slight differences across devices), but struggled most with  low-quality images captured in challenging ambient conditions, i.e., in an indoor environment and with poor lighting. },

keywords = {biometrics, competition IJCB, ocular, sclera, segmentation, SSBC},

pubstate = {published},

tppubtype = {inproceedings}

}