Publications by Alan Lukežič

• A New Dataset and a Distractor-Aware Architecture for Transparent Object Tracking

  Alan Lukežič, Žiga Trojer, Jiří Matas, and Matej Kristan

  International Journal of Computer Vision, Springer, 2024
• A Discriminative Single-Shot Segmentation Network for Visual Object Tracking

  Alan Lukežič, Jiří Matas, and Matej Kristan

  IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
• Performance Evaluation Methodology for Long-Term Single Object Tracking

  Alan Lukežič, Luka Čehovin Zajc, Tomáš Vojíř, Jiří Matas, and Matej Kristan

  IEEE Transactions on Cybernetics, 2020
• Discriminative Correlation Filter Tracker with Channel and Spatial Reliability

  Alan Lukežič, Tomas Vojir, Luka Čehovin Zajc, Jiri Matas, and Matej Kristan

  International Journal of Computer Vision, Springer, 2018
• Deformable Parts Correlation Filters for Robust Visual Tracking

  Alan Lukežič, Luka Čehovin Zajc, and Matej Kristan

  IEEE Transactions on Cybernetics, 2017
• Generalized-Scale Object Counting with Gradual Query Aggregation

  Jer Pelhan, Alan Lukežič, and Matej Kristan

  2025
• A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation

  Jer Pelhan, Alan Lukežič, Vitjan Zavrtanik, and Matej Kristan

  The Thirty-Eighth Annual Conference on Neural Information Processing Systems, NeurIPS2024, 2024
• The Second Visual Object Tracking Segmentation VOTS2024 Challenge Results

  Matej Kristan, Jiri Matas, Pavel Tokmakov, Michael Felsberg, Luka Čehovin Zajc, Alan Lukežič, Khanh-Tung Tran, Xuan-Son Vu, Johanna Bjorklund et al.

  European conference on computer vision workshops, VOTS2024 workshop, 2024
• Tracking and Segmentation of Transparent Objects

  Alan Lukežič and Matej Kristan

  ERK, 2024
• A Detect-and-Verify Paradigm for Low-Shot Counting - DAVE

  Jer Pelhan, Alan Lukežič, Vitjan Zavrtanik, and Matej Kristan

  IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024
• A Low-Shot Object Counting Network With Iterative Prototype Adaptation

  Nikola Djukic, Alan Lukežič, Vitjan Zavrtanik, and Matej Kristan

  ICCV2023, 2023
• The Tenth Visual Object Tracking VOT2022 Challenge Results

  Matej Kristan, Ales Leonardis, Jiri Matas, Michael Felsberg, Roman Pflugfelder, Joni-Kristian Kamarainen, Hyung Jin Chang, Martin Danelljan, Luka Čehovin Zajc et al.

  ECCV Workshops 2022, 2022
• Trans2k: Unlocking the Power of Deep Models for Transparent Object Tracking

  Alan Lukežič, Žiga Trojer, Jiří Matas, and Matej Kristan

  In Proceedings of the British Machine Vision Conference (BMVC), 2022
• A Long-Term Discriminative Single Shot Segmentation Tracker

  Benjamin Džubur, Alan Lukežič, and Matej Kristan

  International Electrotechnical and Computer Science Conference (ERK), 2022
• The Ninth Visual Object Tracking VOT2021 Challenge Results

  Matej Kristan, Jirı Matas, Aleš Leonardis, Michael Felsberg, Roman Pflugfelder, Joni-Kristian Kamarainen, Hyung Jin Chang, Martin Danelljan, Luka Čehovin Zajc et al.

  VOT2021 challenge workshop, ICCV workshops, 2021
• D3S - A Discriminative Single Shot Segmentation Tracker

  Alan Lukežič, Jiří Matas, and Matej Kristan

  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020
• CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark

  Alan Lukežič, Ugur Kart, Jani Käpylä, Ahmed Durmush, Joni-Kristian Kämäräinen, Jiří Matas, and Matej Kristan

  IEEE International Conference on Computer Vision (ICCV), 2019
• Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters

  Ugur Kart, Alan Lukežič, Matej Kristan, Joni-Kristian Kamarainen, and Jiri Matas

  Computer Vision and Pattern Recognition (CVPR), 2019
• Improving Traffic Sign Detection with Temporal Information

  Domen Tabernik, Jon Muhovic, Alan Lukežič, and Danijel Skočaj

  Proceedings of the 23rd Computer Vision Winter Workshop, 2018
• FuCoLoT - A Fully-Correlational Long-Term Tracker

  Alan Lukežič, Luka Čehovin Zajc, Tomas Vojir, Jiri Matas, and Matej Kristan

  Asian Conference on Computer Vision, 2018