| CIAGAN: Conditional Identity Anonymization Generative Adversarial Networks M Maximov*, I Elezi*, L Leal-Taixé Conference on Computer Vision and Pattern Recognition (CVPR) 2020, 5447-5456, 2020 | 319 | 2020 |
| Active Learning for Deep Object Detection via Probabilistic Modeling J Choi, I Elezi, HJ Lee, C Farabet, JM Alvarez International Conference on Computer Vision (ICCV) 2021, 2021 | 197 | 2021 |
| Simple cues lead to a strong multi-object tracker J Seidenschwarz, G Brasó, VC Serrano, I Elezi, L Leal-Taixé Conference on Computer Vision and Pattern Recognition (CVPR) 2023, 13813-13823, 2023 | 129 | 2023 |
| Learning Intra-Batch Connections for Deep Metric Learning J Seidenschwarz, I Elezi, L Leal-Taixé International Conference on Machine Learning (ICML) 2021, 2021 | 89 | 2021 |
| The Group Loss for Deep Metric Learning I Elezi, S Vascon, A Torcinovich, M Pelillo, L Leal-Taixe European Conference on Computer Vision (ECCV) 2020, 2020 | 82 | 2020 |
| Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object Detection I Elezi, Z Yu, A Anandkumar, L Leal-Taixe, JM Alvarez Conference on Computer Vision and Pattern Recognition (CVPR) 2022, 2022 | 67 | 2022 |
| Deepscores-a dataset for segmentation, detection and classification of tiny objects L Tuggener, I Elezi, J Schmidhuber, M Pelillo, T Stadelmann 2018 24th International Conference on Pattern Recognition (ICPR), 3704-3709, 2018 | 67 | 2018 |
| Deep watershed detector for music object recognition L Tuggener, I Elezi, J Schmidhuber, T Stadelmann Proceedings of the 19th International Society for Music Information …, 2018 | 58 | 2018 |
| Deep learning in the wild T Stadelmann, M Amirian, I Arabaci, M Arnold, GF Duivesteijn, I Elezi, ... IAPR Workshop on Artificial Neural Networks in Pattern Recognition, 17-38, 2018 | 57 | 2018 |
| The 2021 image similarity dataset and challenge M Douze, G Tolias, E Pizzi, Z Papakipos, L Chanussot, F Radenovic, ... arXiv preprint arXiv:2106.09672, 2021 | 51 | 2021 |
| The 2021 image similarity dataset and challenge M Douze, G Tolias, E Pizzi, Z Papakipos, L Chanussot, F Radenovic, ... arXiv preprint arXiv:2106.09672, 2021 | 41* | 2021 |
| Transductive label augmentation for improved deep network learning I Elezi*, A Torcinovich*, S Vascon*, M Pelillo 2018 24th International Conference on Pattern Recognition (ICPR), 1432-1437, 2018 | 37 | 2018 |
| Learning neural models for end-to-end clustering BB Meier, I Elezi, M Amirian, O Dürr, T Stadelmann IAPR Workshop on Artificial Neural Networks in Pattern Recognition, 126-138, 2018 | 32 | 2018 |
| Improving Knowledge Distillation using Orthogonal Projections R Miles, I Elezi, J Deng Conference on Computer Vision and Pattern Recognition (CVPR) 2024, 2024 | 24 | 2024 |
| Revealing structure in large graphs: Szemerédi’s regularity lemma and its use in pattern recognition M Pelillo, I Elezi, M Fiorucci Pattern Recognition Letters 87, 4-11, 2017 | 23 | 2017 |
| The group loss++: A deeper look into group loss for deep metric learning I Elezi, J Seidenschwarz, L Wagner, S Vascon, A Torcinovich, M Pelillo, ... IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 2505-2518, 2023 | 21 | 2023 |
| Three Heads Are Better Than One: Complementary Experts for Long-Tailed Semi-supervised Learning C Ma, I Elezi, J Deng, W Dong, C Xu Proceedings of the The 38th Annual AAAI Conference on Artificial Intelligence, 2024 | 20 | 2024 |
| VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections R Miles, P Reddy, I Elezi, J Deng Advances in Neural Information and Processing Systems (NeurIPS), 2024 | 18* | 2024 |
| Learning to Discover and Detect Objects V Fomenko, I Elezi, D Ramanan, L Leal-Taixé, A Ošep Neural Information and Processing Systems (NeurIPS) 2022, 2022 | 16 | 2022 |
| The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes P Kocsis, P Súkeník, G Brasó, M Nießner, L Leal-Taixé, I Elezi Neural Information and Processing Systems (NeurIPS) 2022, 2022 | 10 | 2022 |
Laura Leal-TaixéSenior Research Manager at NVIDIA. Prev. Prof. TU MunichVerified email at tum.de
