Recovery of Superquadrics from Range Images using Deep Learning: A Preliminary Study. - Tim Oblak; Klemen Grm; Ales Jaklic; Peter Peer; Vitomir Struc; Franc Solina (IWOBI, 2019)

Segmentation and Recovery of Superquadric Models using Convolutional Neural Networks. - Jaka Sircelj; Tim Oblak; Klemen Grm; Uros Petkovic; Ales Jaklic; Peter Peer; Vitomir Struc; Franc Solina (CoRR, 2020)

Fingermark Quality Assessment: An Open-Source Toolbox. - Tim Oblak; Rudolf Haraksim; Laurent Beslay; Peter Peer (BIOSIG, 2021)

Automatic Latent Fingerprint Segmentation Using Convolutional Neural Networks. - Leon Premk; Ziga Emersic; Tim Oblak (MIPRO, 2021)

Learning to Predict Superquadric Parameters From Depth Images With Explicit and Implicit Supervision. - Tim Oblak; Jaka Sircelj; Vitomir Struc; Peter Peer; Franc Solina; Ales Jaklic (IEEE Access, 2021)

Fingermark quality assessment framework with classic and deep learning ensemble models. - Tim Oblak; Rudolf Haraksim; Peter Peer; Laurent Beslay (Knowl. Based Syst., 2022)

Probabilistic Fingermark Quality Assessment with Quality Region Localisation. - Tim Oblak; Rudolf Haraksim; Laurent Beslay; Peter Peer (Sensors, 2023)

Latent in the Wild Fingerprint Recognition Competition. - Xinwei Liu 001; Renfang Wang; Tim Oblak; Lara Anzur; Peter Peer; Evaldas Borcovas; Kiran B. Raja (IJCB, 2024)

Minutiae-Informed Contrastive Learning for Fingermark Recognition. - Lara Anzur; Peter Peer; Tim Oblak (ICAIIC, 2025)

Fingerprint image scale estimation for forensic identification systems. - Tim Oblak; Jovana Videnovic; Haris Kupinic; Vitomir Struc; Peter Peer; Ziga Emersic (Int. J. Comput. Commun. Control, 2025)