| Evaluating the search phase of neural architecture search K Yu, C Sciuto, M Jaggi, C Musat, M Salzmann International Conference on Learning Representations, 2020 | 383* | 2020 |
| 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 Advances in Neural Information Processing Systems 35, 10421-10434, 2022 | 190 | 2022 |
| 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 | 112 | 2019 |
| 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 | 78 | 2022 |
| Second-order convolutional neural networks K Yu, M Salzmann arXiv preprint arXiv:1703.06817, 2017 | 69 | 2017 |
| Statistically-motivated second-order pooling K Yu, M Salzmann Proceedings of the European Conference on Computer Vision (ECCV), 600-616, 2018 | 55 | 2018 |
| 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 | 39 | 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 | 39 | 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 | 38 | 2019 |
| 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 | 37 | 2021 |
| Benchmarking the robustness of lidar-camera fusion for 3d object detection K Yu, T Tao, H Xie, Z Lin, T Liang, B Wang, P Chen, D Hao, Y Wang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 32 | 2023 |
| 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 | 30 | 2020 |
| 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 | 27 | 2023 |
| 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 | 19 | 2021 |
| BEVControl: Accurately controlling street-view elements with multi-perspective consistency via bev sketch layout K Yang, E Ma, J Peng, Q Guo, D Lin, K Yu arXiv preprint arXiv:2308.01661, 2023 | 16 | 2023 |
| Fusionad: Multi-modality fusion for prediction and planning tasks of autonomous driving T Ye, W Jing, C Hu, S Huang, L Gao, F Li, J Wang, K Guo, W Xiao, W Mao, ... arXiv preprint arXiv:2308.01006, 2023 | 11 | 2023 |
| Bevheight++: Toward robust visual centric 3d object detection L Yang, T Tang, J Li, P Chen, K Yuan, L Wang, Y Huang, X Zhang, K Yu arXiv preprint arXiv:2309.16179, 2023 | 9 | 2023 |
| 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 | 7 | 2023 |
| 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 | 7 | 2021 |
| Dyn-e: Local appearance editing of dynamic neural radiance fields S Zhang, S Peng, Y ShenTu, Q Shuai, T Chen, K Yu, H Bao, X Zhou arXiv preprint arXiv:2307.12909, 2023 | 6 | 2023 |
Mathieu SalzmannEPFL在 epfl.ch 的電子郵件地址已通過驗證
