13133 / 13162 - Publications - 2018

13133 / 13162 - Visual Recognition Group

Publications 2018

Papers in WoS Journals

FRANC, V. and J. ČECH. Learning CNNs from Weakly Annotated Facial Images. Image and Vision Computing. 2018, 77 10-20. ISSN 0262-8856. DOI 10.1016/j.imavis.2018.06.011.

LUKEŽIČ, A., et al. Discriminative Correlation Filter Tracker with Channel and Spatial Reliability. International Journal of Computer Vision. 2018, 126(7), 671-688. ISSN 0920-5691. DOI 10.1007/s11263-017-1061-3.

TOLIAS, G. and O. CHUM. Efficient Contour Match Kernel. Image and Vision Computing. 2018, 76 14-26. ISSN 0262-8856. DOI 10.1016/j.imavis.2018.04.006.

BARÁTH, D. and L. HAJDER. Efficient Recovery of Essential Matrix From Two Affine Correspondences. IEEE Transactions on Image Processing. 2018, 27(11), 5328-5337. ISSN 1057-7149. DOI 10.1109/TIP.2018.2849866.

KILEEL, J., et al. Distortion Varieties. Foundations of Computational Mathematics. 2018, 18(4), 1043-1071. ISSN 1615-3375. DOI 10.1007/s10208-017-9361-0.

ŠRAJER, F., Z. KÚKELOVÁ, and A. FITZGIBBON. A benchmark of selected algorithmic differentiation tools on some problems in computer vision and machine learning. Optimization Methods and Software. 2018, 2018(33), 889-906. ISSN 1029-4937. DOI 10.1080/10556788.2018.1435651. Available from: https://www.semanticscholar.org/paper/A-benchmark-of-selected-algorithmic-differentiation-Srajer-Kukelova/36b377c6f5e096728005967e7a2c2a4f0951629e

BARÁTH, D. Efficient energy-based topological outlier rejection. Computer Vision and Image Understanding. 2018, 174 70-81. ISSN 1077-3142. DOI 10.1016/j.cviu.2018.07.002.

Books, Book Chapters and Lecture Notes

KÚKELOVÁ, Z. and J. ŠKOVIEROVÁ, eds. Proceedings of the 23rd Computer Vision Winter Workshop. Český Krumlov, 2018-02-05/2018-02-07. Praha: Czech Society for Cybernetics and Informatics, 2018. ISBN 978-80-270-3395-9. Available from: http://cmp.felk.cvut.cz/cvww2018/

BONNET, P., et al. Plant Identification: Experts vs. Machines in the Era of Deep Learning. In: Multimedia Tools and Applications for Environmental & Biodiversity Informatics. Springer, Cham, 2018. p. 131-149. ISBN 978-3-319-76444-3. DOI 10.1007/978-3-319-76445-0_8.

Conference Proceedings

MUSTANIEMI, J., et al. Fast Motion Deblurring for Feature Detection and Matching Using Inertial Measurements. In: 2018 24rd International Conference on Pattern Recognition (ICPR). Beijing, 2018-08-20/2018-08-24. Piscataway, NJ: IEEE, 2018. p. 3068-3073. ISSN 1051-4651. ISBN 978-1-5386-3788-3. DOI 10.1109/ICPR.2018.8546041.

BARÁTH, D. and J. MATAS. Graph-Cut RANSAC. In: CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition 2018, Salt Lake City, 2018-06-19/2018-06-21. Piscataway, NJ: IEEE, 2018. p. 6733-6741. ISSN 2575-7075. ISBN 978-1-5386-6420-9. DOI 10.1109/CVPR.2018.00704. Available from: http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Graph-Cut_RANSAC_CVPR_2018_paper.pdf

SHEKHOVTSOV, O. and B. FLACH. Normalization of Neural Networks using Analytic Variance Propagation. In: KÚKELOVÁ, Z. and J. ŠKOVIEROVÁ, eds. Proceedings of the 23rd Computer Vision Winter Workshop. CVWW 2018: Computer Vision Winter Workshop, Český Krumlov, 2018-02-05/2018-02-07. Praha: Czech Society for Cybernetics and Informatics, 2018. p. 45-53. ISBN 978-80-270-3395-9. Available from: https://arxiv.org/abs/1803.10560

ISCEN, A., et al. Mining on Manifolds: Metric Learning without Labels. In: CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition 2018, Salt Lake City, 2018-06-19/2018-06-21. Piscataway, NJ: IEEE, 2018. p. 7642-7651. ISSN 2575-7075. ISBN 978-1-5386-6420-9. DOI 10.1109/CVPR.2018.00797. Available from: https://ieeexplore.ieee.org/document/8578895

RAZINKOV, E., I. SAVELEVA, and J. MATAS. ALFA: Agglomerative Late Fusion Algorithm for Object Detection. In: 2018 24rd International Conference on Pattern Recognition (ICPR). Beijing, 2018-08-20/2018-08-24. Piscataway, NJ: IEEE, 2018. p. 2594-2599. ISSN 1051-4651. ISBN 978-1-5386-3788-3. DOI 10.1109/ICPR.2018.8545182.

KUPYN, O., et al. DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. In: CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition 2018, Salt Lake City, 2018-06-19/2018-06-21. Piscataway, NJ: IEEE, 2018. p. 8183-8192. ISSN 2575-7075. ISBN 978-1-5386-6420-9. Available from: http://openaccess.thecvf.com/content_cvpr_2018/papers/Kupyn_DeblurGAN_Blind_Motion_CVPR_2018_paper.pdf

ISCEN, A. and O. CHUM. Local Orthogonal-Group Testing. In: FERRARI, V., et al., eds. ECCV2018: Proceedings of the European Conference on Computer Vision, Part II. ECCV2018: European Conference on Computer Vision, Munich, 2018-09-08/2018-09-14. Cham: Springer International Publishing, 2018. p. 460-476. Image Processing, Computer Vision, Pattern Recognition, and Graphics. vol. 11206. ISSN 0302-9743. ISBN 978-3-030-01215-1. DOI 10.1007/978-3-030-01216-8_28.

TOURANI, S., et al. MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models. In: ECCV2018: Proceedings of the European Conference on Computer Vision, Part IV. ECCV2018: European Conference on Computer Vision, Munich, 2018-09-08/2018-09-14. Berlin: Springer-Verlag, 2018. p. 264-281. Lecture Notes in Computer Science. vol. 11208. ISSN 0302-9743. ISBN 978-3-030-01224-3. DOI 10.1007/978-3-030-01225-0_16.

GOMEZ, R., et al. ICDAR2017 Robust Reading Challenge on COCO-Text. In: 14th IAPR International Conference on Document Analysis and Recognition (ICDAR). The 14th IAPR International Conference on Document Analysis and Recognition, Kyoto, 2017-11-09/2017-11-15. Los Alamitos: IEEE Computer Society, 2018. p. 1435-1443. ISSN 1520-5363. ISBN 978-1-5386-3586-5. DOI 10.1109/ICDAR.2017.234.

ŠPETLÍK, R., J. ČECH, and J. MATAS. Non-contact reflectance photoplethysmography: Progress, limitations, and myths. In: FG 2018: Proceedings of the 13th IEEE International Conference on Automatic Face & Gesture Recognition. FG2018: 13th IEEE International Conference on Automatic Face and Gesture Recognition, Xi’an, 2018-05-15/2018-05-19. Piscataway: IEEE, 2018. p. 702-709. ISSN 2326-5396. ISBN 978-1-5386-2335-0. DOI 10.1109/FG.2018.00111. Available from: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8373904

LARSSON, V., Z. KÚKELOVÁ, and Y. ZHENG. Camera Pose Estimation with Unknown Principal Point. In: CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition 2018, Salt Lake City, 2018-06-19/2018-06-21. Piscataway, NJ: IEEE, 2018. p. 2984-2992. ISSN 2575-7075. ISBN 978-1-5386-6420-9. DOI 10.1109/CVPR.2018.00315. Available from: http://openaccess.thecvf.com/content_cvpr_2018/html/Larsson_Camera_Pose_Estimation_CVPR_2018_paper.html

HODAŇ, T., et al. BOP: Benchmark for 6D Object Pose Estimation. In: ECCV2018: Proceedings of the European Conference on Computer Vision, Part X. ECCV2018: European Conference on Computer Vision, Munich, 2018-09-08/2018-09-14. Springer, Cham, 2018. p. 19-35. Lecture Notes in Computer Vision. vol. 11214. ISSN 0302-9743. ISBN 978-3-030-01248-9. DOI 10.1007/978-3-030-01249-6_2.

ŠPETLÍK, R., et al. Visual Heart Rate Estimation with Convolutional Neural Network. In: BMVC2018: Proceedings of the British Machine Vision Conference. BMVC2018: British Machine Vision Conference, Newcastle upon Tyne, 2018-09-03/2018-09-06. London: British Machine Vision Association, 2018. Available from: http://bmvc2018.org/contents/papers/0271.pdf

PRITTS, J., et al. Radially-Distorted Conjugate Translations. In: CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition 2018, Salt Lake City, 2018-06-19/2018-06-21. Piscataway, NJ: IEEE, 2018. p. 1993-2001. ISSN 2575-7075. ISBN 978-1-5386-6420-9. DOI 10.1109/CVPR.2018.00213. Available from: http://openaccess.thecvf.com/content_cvpr_2018/papers_backup/Pritts_Radially-Distorted_Conjugate_Translations_CVPR_2018_paper.pdf

LARSSON, V., et al. Beyond Gröbner Bases: Basis Selection for Minimal Solvers. In: CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition 2018, Salt Lake City, 2018-06-19/2018-06-21. Piscataway, NJ: IEEE, 2018. p. 3945-3954. ISSN 2575-7075. ISBN 978-1-5386-6420-9. DOI 10.1109/CVPR.2018.00415. Available from: http://openaccess.thecvf.com/content_cvpr_2018/papers_backup/Larsson_Beyond_GroBner_Bases_CVPR_2018_paper.pdf

RADENOVIĆ, F., G. TOLIAS, and O. CHUM. Deep Shape Matching. In: ECCV2018: Proceedings of the European Conference on Computer Vision, Part V. ECCV2018: European Conference on Computer Vision, Munich, 2018-09-08/2018-09-14. Springer, Cham, 2018. p. 774-791. Lecture Notes in Computer Science. vol. 11209. ISSN 0302-9743. ISBN 978-3-030-01227-4. DOI 10.1007/978-3-030-01228-1_46.

JAHODA, P., et al. Detecting decision ambiguity from facial images. In: FG 2018: Proceedings of the 13th IEEE International Conference on Automatic Face & Gesture Recognition. FG2018: 13th IEEE International Conference on Automatic Face and Gesture Recognition, Xi’an, 2018-05-15/2018-05-19. Piscataway: IEEE, 2018. p. 499-503. ISSN 2326-5396. ISBN 978-1-5386-2335-0. DOI 10.1109/FG.2018.00080. Available from: http://cmp.felk.cvut.cz/ftp/articles/cech/Jahoda-FG-2018.pdf

NEUMANN, L., A. VEDALDI, and A. ZISSERMAN. Relaxed softmax: Efficient confidence auto-calibration for safe pedestrian detection. In: NIPS 2018 Workshop MLITS. Massachusetts: OpenReview.net / University of Massachusetts, 2018.

NAISER, F., M. ŠMÍD, and J. MATAS. Tracking and Re-Identification System for Multiple Laboratory Animals. In: 2018 VAIB (ICPR2018 Workshop). 2018 24rd International Conference on Pattern Recognition (ICPR), Beijing, 2018-08-20/2018-08-24. Edinburgh: University of Edinburg, 2018. Available from: http://homepages.inf.ed.ac.uk/rbf/VAIB18PAPERS/vaib18naiser.pdf

GOËAU, H., et al. Deep learning for plant identification: how the web can compete with human experts. In: Biodiversity Information Science and Standards 2: e25637. PenSoft, 2018. DOI 10.3897/biss.2.25637. Available from: https://biss.pensoft.net/article/25637/list/8/

ŠULC, M., L. PICEK, and J. MATAS. Plant Recognition by Inception Networks with Test-time Class Prior Estimation. In: CAPPELLATO, L., et al., eds. Working Notes of CLEF 2018 - Conference and Labs of the Evaluation Forum. CLEF 2018: Conference and Labs of the Evaluation Forum, Avignon, 2018-09-10/2018-09-14. CEUR-WS.org, 2018. vol. 2125. ISSN 1613-0073. Available from: http://ceur-ws.org/Vol-2125/paper_152.pdf

ISCEN, A., et al. Fast Spectral Ranking for Similarity Search. In: CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition 2018, Salt Lake City, 2018-06-19/2018-06-21. Piscataway, NJ: IEEE, 2018. p. 7632-7641. ISSN 2575-7075. ISBN 978-1-5386-6420-9. DOI 10.1109/CVPR.2018.00796. Available from: https://ieeexplore.ieee.org/document/8578894

KART, U., et al. Depth Masked Discriminative Correlation Filter. In: 2018 24rd International Conference on Pattern Recognition (ICPR). Beijing, 2018-08-20/2018-08-24. Piscataway, NJ: IEEE, 2018. p. 2112-2117. ISSN 1051-4651. ISBN 978-1-5386-3788-3. DOI 10.1109/ICPR.2018.8546179.

MISHKIN, D., F. RADENOVIĆ, and J. MATAS. Repeatability Is Not Enough: Learning Affine Regions via Discriminability. In: ECCV2018: Proceedings of the European Conference on Computer Vision, Part IX. ECCV2018: European Conference on Computer Vision, Munich, 2018-09-08/2018-09-14. Springer, Cham, 2018. p. 287-304. Lecture Notes in Computer Vision. vol. 11213. ISSN 0302-9743. ISBN 978-3-030-01239-7. DOI 10.1007/978-3-030-01240-3_18.

RADENOVIĆ, F., et al. Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking. In: CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition 2018, Salt Lake City, 2018-06-19/2018-06-21. Piscataway, NJ: IEEE, 2018. p. 5706-5715. ISSN 2575-7075. ISBN 978-1-5386-6420-9. DOI 10.1109/CVPR.2018.00598. Available from: http://cmp.felk.cvut.cz/~radenfil/publications/Radenovic-CVPR18.pdf

SIMEONI, O., et al. Unsupervised object discovery for instance recognition. In: 2018 IEEE Winter Conference on Applications of Computer Vision, WACV 2018. WACV: 2018 IEEE Winter Conference on Applications of Computer Vision, Lake Tahoe, 2018-03-12/2018-02-15. Institute of Electrical and Electronics Engineers Inc, 2018. p. 1745-1754. ISSN 2472-6737. ISBN 978-1-5386-4886-5. DOI 10.1109/WACV.2018.00194.

BARÁTH, D. and J. MATAS. Multi-class Model Fitting by Energy Minimization and Mode-Seeking. In: ECCV2018: Proceedings of the European Conference on Computer Vision, Part XVI. ECCV2018: European Conference on Computer Vision, Munich, 2018-09-08/2018-09-14. Springer, Cham, 2018. p. 229-245. Lecture Notes in Computer Vision. vol. 11220. ISSN 0302-9743. ISBN 978-3-030-01269-4. DOI 10.1007/978-3-030-01270-0_14.

Dissertations

VOJÍŘ, T. Short-Term Visual Object Tracking in Real-Time. Praha: Defense date 2018-02-28. PhD Thesis. ČVUT FEL, Katedra kybernetiky - Centrum strojového vnímání. Supervised by J. MATAS.

Research Reports

RADENOVIĆ, F., et al. Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking. [Research Report] ArXiv, 2018. Report no. arXiv:1803.11285.

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