Imbalance problems in object detection: A review K Oksuz, BC Cam, S Kalkan, E Akbas IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (10), 3388 …, 2020 | 502 | 2020 |
Localization recall precision (LRP): A new performance metric for object detection K Oksuz, BC Cam, E Akbas, S Kalkan Proceedings of the European conference on computer vision (ECCV), 504-519, 2018 | 135 | 2018 |
Rank & sort loss for object detection and instance segmentation K Oksuz, BC Cam, E Akbas, S Kalkan Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 49 | 2021 |
A ranking-based, balanced loss function unifying classification and localisation in object detection K Oksuz, BC Cam, E Akbas, S Kalkan Advances in Neural Information Processing Systems 2020, 15534-15545, 2020 | 49 | 2020 |
Generating positive bounding boxes for balanced training of object detectors K Oksuz, BC Cam, E Akbas, S Kalkan Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020 | 31 | 2020 |
One metric to measure them all: Localisation recall precision (lrp) for evaluating visual detection tasks K Oksuz, BC Cam, S Kalkan, E Akbas IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (12), 9446 …, 2021 | 28 | 2021 |
The comparison of the performances of global nearest neighbor and probability hypothesis density filter for varying clutter rates K Öksüz, AT Cemgil 2016 24th Signal Processing and Communication Application Conference (SIU …, 2016 | 8 | 2016 |
Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation K Oksuz, BC Cam, F Kahraman, ZS Baltaci, S Kalkan, E Akbas British Machine Vision Conference, 2021, 2021 | 7 | 2021 |
Multitarget tracking performance metric: deficiency aware subpattern assignment K Oksuz, AT Cemgil IET Radar, Sonar & Navigation 12 (3), 373-381, 2018 | 6 | 2018 |
Towards building self-aware object detectors via reliable uncertainty quantification and calibration K Oksuz, T Joy, PK Dokania Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 4 | 2023 |
Correlation Loss: Enforcing Correlation between Classification and Localization F Kahraman, K Oksuz, S Kalkan, E Akbas AAAI Conference on Artificial Intelligence 2023, 2023 | 3 | 2023 |
MoCaE: Mixture of Calibrated Experts Significantly Improves Object Detection K Oksuz, S Kuzucu, T Joy, PK Dokania arXiv preprint arXiv:2309.14976, 2023 | 1 | 2023 |
Deficiency aware subpattern assignment K Öksüz, AT Cemgil 2017 25th Signal Processing and Communications Applications Conference (SIU …, 2017 | 1 | 2017 |
On Calibration of Object Detectors: Pitfalls, Evaluation and Baselines S Kuzucu, K Oksuz, J Sadeghi, PK Dokania arXiv preprint arXiv:2405.20459, 2024 | | 2024 |
Generalized Mask-aware IoU for Anchor Assignment for Real-time Instance Segmentation BC Çam, K Öksüz, F Kahraman, ZS Baltacı, S Kalkan, E Akbaş arXiv preprint arXiv:2312.17031, 2023 | | 2023 |
Class Uncertainty: A Measure to Mitigate Class Imbalance ZS Baltaci, K Oksuz, S Kuzucu, K Tezoren, BK Konar, A Ozkan, E Akbas, ... arXiv preprint arXiv:2311.14090, 2023 | | 2023 |
Segment, Select, Correct: A Framework for Weakly-Supervised Referring Segmentation F Eiras, K Oksuz, A Bibi, PHS Torr, PK Dokania arXiv preprint arXiv:2310.13479, 2023 | | 2023 |
Identifying and Addressing Imbalance Problems in Visual Detection K Oksuz Middle East Technical University, 2021 | | 2021 |
What Makes Safety Fine-tuning Methods Safe? A Mechanistic Study S Jain, ES Lubana, K Oksuz, T Joy, P Torr, A Sanyal, PK Dokania ICML 2024 Workshop on Mechanistic Interpretability, 0 | | |