| Flownet: Learning optical flow with convolutional networks A Dosovitskiy, P Fischer, E Ilg, P Hausser, C Hazirbas, V Golkov, ... International Conference on Computer Vision (ICCV), 2758-2766, 2015 | 3998* | 2015 |
| FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-based CNN Architecture C Hazirbas, L Ma, C Domokos, D Cremers Asian Conference on Computer Vision (ACCV), 2016 | 624 | 2016 |
| Image-based localization using LSTMs for structured feature correlation F Walch, C Hazirbas, L Leal-Taixé, T Sattler, S Hilsenbeck, D Cremers International Conference on Computer Vision (ICCV), 2017 | 468 | 2017 |
| Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems T Meinhardt, M Möller, C Hazirbas, D Cremers International Conference on Computer Vision (ICCV), 2017 | 304 | 2017 |
| What makes good synthetic training data for learning disparity and optical flow estimation? N Mayer, E Ilg, P Fischer, C Hazirbas, D Cremers, A Dosovitskiy, T Brox International Journal of Computer Vision (IJCV), 1-19, 2018 | 199 | 2018 |
| CAPTCHA Recognition with Active Deep Learning F Stark, C Hazirbas, R Triebel, D Cremers German Conference on Pattern Recognition Workshop (GCPRW), 94, 2015 | 122 | 2015 |
| Deep depth from focus C Hazirbas, SG Soyer, MC Staab, L Leal-Taixé, D Cremers Asian Conference on Computer Vision (ACCV), 2018 | 81 | 2018 |
| Towards measuring fairness in AI: the Casual Conversations dataset C Hazirbas, J Bitton, B Dolhansky, J Pan, A Gordo, CC Ferrer arXiv preprint arXiv:2104.02821, 2021 | 45* | 2021 |
| Image-based localization with spatial LSTMs F Walch, C Hazirbas, L Leal-Taixé, T Sattler, S Hilsenbeck, D Cremers International Conference on Computer Vision (ICCV) 2, 2017 | 29 | 2017 |
| Smagt P. vd, Cremers D., and Brox T.,“ A Dosovitskiy, P Fischer, E Ilg, P Häusser, C Hazırbaş, V Golkov Flownet: Learning optical flow with convolutional networks,” in 2015 IEEE …, 2015 | 17 | 2015 |
| Interactive Multi-label Segmentation of RGB-D Images J Diebold, N Demmel, C Hazirbas, M Möller, D Cremers Scale Space and Variational Methods in Computer Vision (SSVM), 294-306, 2015 | 15 | 2015 |
| Towards measuring fairness in speech recognition: casual conversations dataset transcriptions C Liu, M Picheny, L Sarı, P Chitkara, A Xiao, X Zhang, M Chou, ... ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 10 | 2022 |
| Generating high fidelity data from low-density regions using diffusion models V Sehwag, C Hazirbas, A Gordo, F Ozgenel, C Canton Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 10 | 2022 |
| Deep Learning for Image-Based Localization F Walch, D Cremers, S Hilsenbeck, C Hazirbas, L Leal-Taixé Master’s thesis, 2016 | 8 | 2016 |
| Fairness indicators for systematic assessments of visual feature extractors P Goyal, AR Soriano, C Hazirbas, L Sagun, N Usunier 2022 ACM Conference on Fairness, Accountability, and Transparency, 70-88, 2022 | 6 | 2022 |
| ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations BY Idrissi, D Bouchacourt, R Balestriero, I Evtimov, C Hazirbas, N Ballas, ... arXiv preprint arXiv:2211.01866, 2022 | 5 | 2022 |
| Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation C Hazirbas, J Diebold, D Cremers Scale Space and Variational Methods in Computer Vision (SSVM) 9087, 243-255, 2015 | 5* | 2015 |
| Localized Uncertainty Attacks OA Dia, T Karaletsos, C Hazirbas, CC Ferrer, IK Kabul, E Meijer CVPRW on Adversarial Machine Learning in Real-World Computer Vision Systems …, 2021 | 2 | 2021 |
| Image processing using a convolutional neural network C Schroers, F Perazzi, C Hazirbas US Patent 10,706,503, 2020 | 1 | 2020 |
| The Casual Conversations v2 Dataset B Porgali, V Albiero, J Ryda, CC Ferrer, C Hazirbas arXiv preprint arXiv:2303.04838, 2023 | | 2023 |
Daniel CremersTechnical University of MunichVerified email at tum.de
