| Evaluating the search phase of neural architecture search K Yu, C Sciuto, M Jaggi, C Musat, M Salzmann International Conference on Learning Representations, 2020 | 313* | 2020 |
| Recurrent U-Net for resource-constrained segmentation W Wang, K Yu, J Hugonot, P Fua, M Salzmann Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 90 | 2019 |
| Second-order convolutional neural networks K Yu, M Salzmann arXiv preprint arXiv:1703.06817, 2017 | 63 | 2017 |
| Statistically-motivated second-order pooling K Yu, M Salzmann Proceedings of the European Conference on Computer Vision (ECCV), 600-616, 2018 | 50 | 2018 |
| Bevfusion: A simple and robust lidar-camera fusion framework T Liang, H Xie, K Yu, Z Xia, Z Lin, Y Wang, T Tang, B Wang, Z Tang arXiv preprint arXiv:2205.13790, 2022 | 49 | 2022 |
| Generalized class incremental learning F Mi, L Kong, T Lin, K Yu, B Faltings Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 31 | 2020 |
| Overcoming multi-model forgetting Y Benyahia, K Yu, KB Smires, M Jaggi, AC Davison, M Salzmann, ... International Conference on Machine Learning, 594-603, 2019 | 31 | 2019 |
| How to train your super-net: An analysis of training heuristics in weight-sharing nas K Yu, R Ranftl, M Salzmann arXiv preprint arXiv:2003.04276, 2020 | 28 | 2020 |
| Knowledge distillation via the target-aware transformer S Lin, H Xie, B Wang, K Yu, X Chang, X Liang, G Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 27 | 2022 |
| Pyramid architecture search for real-time image deblurring X Hu, W Ren, K Yu, K Zhang, X Cao, W Liu, B Menze Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 24 | 2021 |
| Nas-bench-suite: NAS evaluation is (now) surprisingly easy Y Mehta, C White, A Zela, A Krishnakumar, G Zabergja, S Moradian, ... arXiv preprint arXiv:2201.13396, 2022 | 16 | 2022 |
| Landmark regularization: Ranking guided super-net training in neural architecture search K Yu, R Ranftl, M Salzmann Proceedings of the IEEE/CVF Conference on computer vision and pattern …, 2021 | 16 | 2021 |
| Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection K Yu, T Tao, H Xie, Z Lin, Z Wu, Z Xia, T Liang, H Sun, J Deng, D Hao, ... arXiv preprint arXiv:2205.14951, 2022 | 10 | 2022 |
| An analysis of super-net heuristics in weight-sharing NAS K Yu, R Ranftl, M Salzmann IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 8110 …, 2021 | 3 | 2021 |
| BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection L Yang, K Yu, T Tang, J Li, K Yuan, L Wang, X Zhang, P Chen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 1 | 2023 |
| Beyond One Glance: Gated Recurrent Architecture for Hand Segmentation W Wang, K Yu, J Hugonot, P Fua, M Salzmann arXiv preprint arXiv:1811.10914, 2018 | 1 | 2018 |
| LiDAR-NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields T Tao, L Gao, G Wang, P Chen, D Hao, X Liang, M Salzmann, K Yu arXiv preprint arXiv:2304.10406, 2023 | | 2023 |
| Painting 3D Nature in 2D: View Synthesis of Natural Scenes from a Single Semantic Mask S Zhang, S Peng, T Chen, L Mou, H Lin, K Yu, Y Liao, X Zhou Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | | 2023 |
| DARTS Once More: Enhancing Differentiable Architecture Search by Masked Image Modeling B Guo, S Guo, M Shi, P Chen, S He, J Chen, K Yu arXiv preprint arXiv:2211.10105, 2022 | | 2022 |
| Learning Self-Regularized Adversarial Views for Self-Supervised Vision Transformers T Tang, C Li, G Wang, K Yu, X Chang, X Liang arXiv preprint arXiv:2210.08458, 2022 | | 2022 |
Mathieu SalzmannEPFLVerified email at epfl.ch
