| Learning video object segmentation from static images A Khoreva, F Perazzi, R Benenson, B Schiele, A Sorkine-Hornung IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2 (7), 2017 | 306* | 2017 |
| Simple does it: Weakly supervised instance and semantic segmentation A Khoreva, R Benenson, J Hosang, M Hein, B Schiele IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 288 | 2017 |
| Exploiting saliency for object segmentation from image level labels S Joon Oh, R Benenson, A Khoreva, Z Akata, M Fritz, B Schiele IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 4410-4419, 2017 | 110* | 2017 |
| Lucid data dreaming for object tracking A Khoreva, R Benenson, E Ilg, T Brox, B Schiele The DAVIS Challenge on Video Object Segmentation, 2017 | 89 | 2017 |
| Lucid data dreaming for video object segmentation A Khoreva, R Benenson, E Ilg, T Brox, B Schiele International Journal of Computer Vision 127 (9), 1175-1197, 2019 | 71* | 2019 |
| Classifier based graph construction for video segmentation A Khoreva, F Galasso, M Hein, B Schiele IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 951-960, 2015 | 57 | 2015 |
| Learning to Refine Human Pose Estimation M Fieraru, A Khoreva, L Pishchulin, B Schiele IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops …, 2018 | 48 | 2018 |
| Weakly Supervised Object Boundaries A Khoreva, R Benenson, M Omran, M Hein, B Schiele IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 183-192, 2016 | 37 | 2016 |
| Video Object Segmentation with Language Referring Expressions A Khoreva, A Rohrbach, B Schiele Asian Conference on Computer Vision (ACCV), 2018 | 31 | 2018 |
| Learning must-link constraints for video segmentation based on spectral clustering A Khoreva, F Galasso, M Hein, B Schiele German Conference on Pattern Recognition, 701-712, 2014 | 26 | 2014 |
| Improved image boundaries for better video segmentation A Khoreva, R Benenson, F Galasso, M Hein, B Schiele European Conference on Computer Vision, 773-788, 2016 | 16 | 2016 |
| Choice of finite differences in finding the goal function gradient in the estimation procedures of interframe image deformations AG Tashlinskii, AM Horeva Pattern Recognition and Image Analysis 21 (2), 343-346, 2011 | 16* | 2011 |
| A U-Net Based Discriminator for Generative Adversarial Networks E Schönfeld, B Schiele, A Khoreva IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 6 | 2020 |
| Уменьшение вычислительных затрат при идентификации местоположения фрагментов на больших изображениях АГ Ташлинский, ИН Кавеев, АМ Хорева Инфокоммуникационные технологии 8 (3), 73-76, 2010 | 6 | 2010 |
| Progressive Augmentation of GANs D Zhang, A Khoreva Neural Information Processing Systems (NeurIPS), 2019 | 4* | 2019 |
| Short-Term Prediction and Multi-Camera Fusion on Semantic Grids L Hoyer, P Kesper, A Khoreva, V Fischer ICCV Workshop on Computer Vision for Road Scene Understanding and Autonomous …, 2019 | 3 | 2019 |
| Grid Saliency for Context Explanations of Semantic Segmentation L Hoyer, M Munoz, P Katiyar, A Khoreva, V Fischer Neural Information Processing Systems (NeurIPS), 2019 | 3 | 2019 |
| Finding the pseudogradient of the objective function in procedures for estimation of interframe deformations of images AM Horeva, AG Tashlinskii, LS Birtimirov Pattern Recognition and Image Analysis 23 (4), 440-444, 2013 | 2 | 2013 |
| Оптимизация псевдоградиента в задаче оценивания межкадровых геометрических деформаций изображений АГ Ташлинский, АМ Хорева, ОА Лазарева Радиоэлектронная техника, 120-124, 2008 | 2 | 2008 |
| 3D Noise and Adversarial Supervision Is All You Need for Multi-Modal Semantic Image Synthesis V Sushko, E Schönfeld, D Zhang, J Gall, B Schiele, A Khoreva European Conference on Computer Vision (ECCV) Workshops, 2020 | | 2020 |
Bernt SchieleProfessor, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarland UniversityVerified email at mpi-inf.mpg.de
