Alexander Kolesnikov
Lampert Group
9 Publications
2019 | Conference Paper | IST-REx-ID: 7640 |
Kolesnikov A, Kuznetsova A, Lampert C, Ferrari V. Detecting visual relationships using box attention. In: Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE; 2019. doi:10.1109/ICCVW.2019.00217
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2018 | Thesis | IST-REx-ID: 197 |
Kolesnikov A. Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images. 2018. doi:10.15479/AT:ISTA:th_1021
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2018 | Journal Article | IST-REx-ID: 563 |
Ringbauer H, Kolesnikov A, Field D, Barton NH. Estimating barriers to gene flow from distorted isolation-by-distance patterns. Genetics. 2018;208(3):1231-1245. doi:10.1534/genetics.117.300638
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2017 | Conference Paper | IST-REx-ID: 1000 |
Kolesnikov A, Lampert C. PixelCNN models with auxiliary variables for natural image modeling. In: 34th International Conference on Machine Learning. Vol 70. JMLR; 2017:1905-1914.
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2017 | Conference Paper | IST-REx-ID: 998 |
Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. iCaRL: Incremental classifier and representation learning. In: Vol 2017. IEEE; 2017:5533-5542. doi:10.1109/CVPR.2017.587
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2017 | Conference Paper | IST-REx-ID: 911 |
Royer A, Kolesnikov A, Lampert C. Probabilistic image colorization. In: BMVA Press; 2017:85.1-85.12. doi:10.5244/c.31.85
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2016 | Conference Paper | IST-REx-ID: 1102 |
Kolesnikov A, Lampert C. Improving weakly-supervised object localization by micro-annotation. In: Proceedings of the British Machine Vision Conference 2016. Vol 2016-September. BMVA Press; 2016:92.1-92.12. doi:10.5244/C.30.92
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2016 | Conference Paper | IST-REx-ID: 1369 |
Kolesnikov A, Lampert C. Seed, expand and constrain: Three principles for weakly-supervised image segmentation. In: Vol 9908. Springer; 2016:695-711. doi:10.1007/978-3-319-46493-0_42
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2014 | Conference Paper | IST-REx-ID: 2171 |
Kolesnikov A, Guillaumin M, Ferrari V, Lampert C. Closed-form approximate CRF training for scalable image segmentation. In: Fleet D, Pajdla T, Schiele B, Tuytelaars T, eds. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 8691. Springer; 2014:550-565. doi:10.1007/978-3-319-10578-9_36
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9 Publications
2019 | Conference Paper | IST-REx-ID: 7640 |
Kolesnikov A, Kuznetsova A, Lampert C, Ferrari V. Detecting visual relationships using box attention. In: Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE; 2019. doi:10.1109/ICCVW.2019.00217
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2018 | Thesis | IST-REx-ID: 197 |
Kolesnikov A. Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images. 2018. doi:10.15479/AT:ISTA:th_1021
[Published Version]
View
| Files available
| DOI
2018 | Journal Article | IST-REx-ID: 563 |
Ringbauer H, Kolesnikov A, Field D, Barton NH. Estimating barriers to gene flow from distorted isolation-by-distance patterns. Genetics. 2018;208(3):1231-1245. doi:10.1534/genetics.117.300638
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
2017 | Conference Paper | IST-REx-ID: 1000 |
Kolesnikov A, Lampert C. PixelCNN models with auxiliary variables for natural image modeling. In: 34th International Conference on Machine Learning. Vol 70. JMLR; 2017:1905-1914.
[Submitted Version]
View
| Download Submitted Version (ext.)
| WoS
| arXiv
2017 | Conference Paper | IST-REx-ID: 998 |
Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. iCaRL: Incremental classifier and representation learning. In: Vol 2017. IEEE; 2017:5533-5542. doi:10.1109/CVPR.2017.587
[Submitted Version]
View
| DOI
| Download Submitted Version (ext.)
| WoS
2017 | Conference Paper | IST-REx-ID: 911 |
Royer A, Kolesnikov A, Lampert C. Probabilistic image colorization. In: BMVA Press; 2017:85.1-85.12. doi:10.5244/c.31.85
[Published Version]
View
| Files available
| DOI
| arXiv
2016 | Conference Paper | IST-REx-ID: 1102 |
Kolesnikov A, Lampert C. Improving weakly-supervised object localization by micro-annotation. In: Proceedings of the British Machine Vision Conference 2016. Vol 2016-September. BMVA Press; 2016:92.1-92.12. doi:10.5244/C.30.92
[Published Version]
View
| DOI
| Download Published Version (ext.)
2016 | Conference Paper | IST-REx-ID: 1369 |
Kolesnikov A, Lampert C. Seed, expand and constrain: Three principles for weakly-supervised image segmentation. In: Vol 9908. Springer; 2016:695-711. doi:10.1007/978-3-319-46493-0_42
[Preprint]
View
| DOI
| Download Preprint (ext.)
2014 | Conference Paper | IST-REx-ID: 2171 |
Kolesnikov A, Guillaumin M, Ferrari V, Lampert C. Closed-form approximate CRF training for scalable image segmentation. In: Fleet D, Pajdla T, Schiele B, Tuytelaars T, eds. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 8691. Springer; 2014:550-565. doi:10.1007/978-3-319-10578-9_36
[Submitted Version]
View
| DOI
| Download Submitted Version (ext.)