Publications by Matej Kristan

• Keep DRÆMing: Discriminative 3D anomaly detection through anomaly simulation

  Vitjan Zavrtanik, Matej Kristan, and Danijel Skočaj

  Pattern Recognition Letters, 2024
• 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
• eWaSR — An Embedded-Compute-Ready Maritime Obstacle Detection Network

  Matija Tersek, Lojze Žust, and Matej Kristan

  Sensors, MDPI, 2023
• HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic

  Marko Rus, Anja Fettich, Matej Kristan, and Matjaž Ličer

  Geoscientific Model Development, Copernicus Publications, 2023
• Learning with Weak Annotations for Robust Maritime Obstacle Detection

  Lojze Žust and Matej Kristan

  Sensors, MDPI, 2022
• MODS--A USV-Oriented Object Detection and Obstacle Segmentation Benchmark

  Borja Bovcon, Jon Muhovič, Duško Vranac, Dean Mozetič, Janez Perš, and Matej Kristan

  IEEE Transactions on Intelligent Transportation Systems, 2021
• 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
• Prepletanje umetne inteligence in fizike pri napovedovanju obalnih poplav

  Matjaž Ličer, Lojze Žust, and Matej Kristan

  Alternator, 2021
• WaSR -- A Water Segmentation and Refinement Maritime Obstacle Detection Network

  Borja Bovcon and Matej Kristan

  IEEE Transactions on Cybernetics, TCYB, 2021
• Reconstruction by inpainting for visual anomaly detection

  Vitjan Zavrtanik, Matej Kristan, and Danijel Skočaj

  Pattern Recognition, Elsevier, 2021
• HIDRA 1.0: deep-learning-based ensemble sea level forecasting in the northern Adriatic

  Lojze Žust, Anja Fettich, Matej Kristan, and Matjaž Ličer

  Geoscientific Model Development, Copernicus Publications, 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
• A segmentation-based approach for polyp counting in the wild

  Vitjan Zavrtanik, Martin Vodopivec, and Matej Kristan

  Engineering Applications of Artificial Intelligence, Elsevier, 2020
• Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks

  Domen Tabernik, Matej Kristan, and Aleš Leonardis

  International Journal of Computer Vision, 2020
• Obstacle Tracking for Unmanned Surface Vessels using 3D Point Cloud

  Jon Muhovič, Rok Mandeljc, Borja Bovcon, Matej Kristan, and Janez Perš

  Journal of Oceanic Engineering, IEEE, 2019
• Towards automated scyphistoma census in underwater imagery : a useful research and monitoring too

  Martin Vodopivec, Rok Mandeljc, Tihomir Makovec, Alenka Malej, and Matej Kristan

  Journal of sea research, 2018
• Towards automated scyphistoma census in underwater imagery: a useful research and monitoring tool

  Martin Vodopivec, Rok Mandeljc, Tihomir Makovec, Alenka Malej, and Matej Kristan

  Journal of Sea Research, 2018
• Stereo obstacle detection for unmanned surface vehicles by IMU-assisted semantic segmentation

  Borja Bovcon, Rok Mandeljc, Janez Perš, and Matej Kristan

  Robotics and Autonomous Systems, Elsevier, 2018
• 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