| How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks) A Bulat, G Tzimiropoulos The IEEE International Conference on Computer Vision (ICCV), 2017 | 1009 | 2017 |
| Human pose estimation via convolutional part heatmap regression A Bulat, G Tzimiropoulos European Conference on Computer Vision, 717-732, 2016 | 548 | 2016 |
| Large pose 3D face reconstruction from a single image via direct volumetric CNN regression AS Jackson, A Bulat, V Argyriou, G Tzimiropoulos Proceedings of the IEEE International Conference on Computer Vision, 1031-1039, 2017 | 403 | 2017 |
| To learn image super-resolution, use a GAN to learn how to do image degradation first A Bulat, J Yang, G Tzimiropoulos European Conference on Computer Vision, 2018 | 245 | 2018 |
| Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs A Bulat, G Tzimiropoulos Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 240 | 2018 |
| Deep machine learning provides state-of-the-art performance in image-based plant phenotyping MP Pound, JA Atkinson, AJ Townsend, MH Wilson, M Griffiths, ... Gigascience 6 (10), gix083, 2017 | 240 | 2017 |
| Binarized convolutional landmark localizers for human pose estimation and face alignment with limited resources A Bulat, G Tzimiropoulos Proceedings of the IEEE International Conference on Computer Vision, 3706-3714, 2017 | 206 | 2017 |
| XNOR-Net++: Improved binary neural networks A Bulat, G Tzimiropoulos Proceedings of the British Machine Vision Conference (BMVC), 2019 | 105 | 2019 |
| Training binary neural networks with real-to-binary convolutions B Martinez, J Yang, A Bulat, G Tzimiropoulos International Conference on Learning Representations (ICLR), 2020 | 94 | 2020 |
| Two-stage convolutional part heatmap regression for the 1st 3d face alignment in the wild (3dfaw) challenge A Bulat, G Tzimiropoulos European Conference on Computer Vision, 616-624, 2016 | 78 | 2016 |
| Convolutional aggregation of local evidence for large pose face alignment A Bulat, G Tzimiropoulos Proceedings of the British Machine Vision Conference (BMVC), 2016 | 70 | 2016 |
| Toward fast and accurate human pose estimation via soft-gated skip connections A Bulat, J Kossaifi, G Tzimiropoulos, M Pantic 2020 15th IEEE International Conference on Automatic Face & Gesture Recognition, 2020 | 57 | 2020 |
| T-Net: Parametrizing Fully Convolutional Nets with a Single High-Order Tensor J Kossaifi, A Bulat, G Tzimiropoulos, M Pantic IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 49 | 2019 |
| Factorized Higher-Order CNNs with an Application to Spatio-Temporal Emotion Estimation J Kossaifi, A Toisoul, A Bulat, Y Panagakis, TM Hospedales, M Pantic Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 44* | 2020 |
| Estimation of continuous valence and arousal levels from faces in naturalistic conditions A Toisoul, J Kossaifi, A Bulat, G Tzimiropoulos, M Pantic Nature Machine Intelligence, 1-9, 2021 | 32 | 2021 |
| BATS: Binary ArchitecTure Search A Bulat, B Martinez, G Tzimiropoulos European Conference on Computer Vision (ECCV), 2020 | 32 | 2020 |
| Hierarchical binary CNNs for landmark localization with limited resources A Bulat, G Tzimiropoulos IEEE Transactions on Pattern Analysis and Machine Intelligence 42 (2), 343-356, 2020 | 28 | 2020 |
| Improved training of binary networks for human pose estimation and image recognition A Bulat, G Tzimiropoulos, J Kossaifi, M Pantic | 28 | 2019 |
| Knowledge distillation via softmax regression representation learning J Yang, B Martinez, A Bulat, G Tzimiropoulos International Conference on Learning Representations (ICLR), 2021 | 26* | 2021 |
| High-Capacity Expert Binary Networks A Bulat, B Martinez, G Tzimiropoulos International Conference on Learning Representations (ICLR), 2021 | 25 | 2021 |
Georgios (Yorgos) TzimiropoulosAssociate Professor, Queen Mary University of London | Principal Scientist, Samsung AI CenterVerified email at qmul.ac.uk
