| MBLLEN: Low-Light Image/Video Enhancement Using CNNs. F Lv, F Lu, J Wu, C Lim BMVC, 220, 2018 | 711 | 2018 |
| Reflection backdoor: A natural backdoor attack on deep neural networks Y Liu, X Ma, J Bailey, F Lu European Conference on Computer Vision, 182-199, 2020 | 572 | 2020 |
| Understanding adversarial attacks on deep learning based medical image analysis systems X Ma, Y Niu, L Gu, Y Wang, Y Zhao, J Bailey, F Lu Pattern Recognition 110, 107332, 2021 | 497 | 2021 |
| Attention guided low-light image enhancement with a large scale low-light simulation dataset F Lv, Y Li, F Lu International Journal of Computer Vision 129 (7), 2175-2193, 2021 | 304 | 2021 |
| Adaptive linear regression for appearance-based gaze estimation F Lu, Y Sugano, T Okabe, Y Sato IEEE transactions on pattern analysis and machine intelligence 36 (10), 2033 …, 2014 | 258 | 2014 |
| Advancing image understanding in poor visibility environments: A collective benchmark study W Yang, Y Yuan, W Ren, J Liu, WJ Scheirer, Z Wang, T Zhang, Q Zhong, ... IEEE Transactions on Image Processing 29, 5737-5752, 2020 | 228 | 2020 |
| Appearance-based gaze estimation via evaluation-guided asymmetric regression Y Cheng, F Lu, X Zhang Proceedings of the European Conference on Computer Vision (ECCV), 100-115, 2018 | 173 | 2018 |
| Inferring human gaze from appearance via adaptive linear regression F Lu, Y Sugano, T Okabe, Y Sato 2011 International Conference on Computer Vision, 153-160, 2011 | 173 | 2011 |
| Gaze estimation by exploring two-eye asymmetry Y Cheng, X Zhang, F Lu, Y Sato IEEE Transactions on Image Processing 29, 5259-5272, 2020 | 161 | 2020 |
| Appearance-based Gaze Estimation With Deep Learning: A Review and Benchmark Y Cheng, H Wang, Y Bao, F Lu IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 143 | 2024 |
| A coarse-to-fine adaptive network for appearance-based gaze estimation Y Cheng, S Huang, F Wang, C Qian, F Lu Proceedings of the AAAI Conference on Artificial Intelligence 34 (07), 10623 …, 2020 | 134 | 2020 |
| VoxSegNet: Volumetric CNNs for semantic part segmentation of 3D shapes Z Wang, F Lu IEEE transactions on visualization and computer graphics 26 (9), 2919-2930, 2019 | 132 | 2019 |
| Detail preserving depth estimation from a single image using attention guided networks Z Hao, Y Li, S You, F Lu 2018 International Conference on 3D Vision (3DV), 304-313, 2018 | 123 | 2018 |
| Unsupervised learning for intrinsic image decomposition from a single image Y Liu, Y Li, S You, F Lu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 119 | 2020 |
| Learning gaze biases with head motion for head pose-free gaze estimation F Lu, T Okabe, Y Sugano, Y Sato Image and Vision Computing 32 (3), 169-179, 2014 | 118 | 2014 |
| A head pose-free approach for appearance-based gaze estimation. F Lu, T Okabe, Y Sugano, Y Sato BMVC, 1-11, 2011 | 117 | 2011 |
| Gaze Estimation using Transformer Y Cheng, F Lu Proceedings of International Conference on Pattern Recognition (ICPR), 2022 | 99 | 2022 |
| Real-time semantic segmentation via multiply spatial fusion network H Si, Z Zhang, F Lv, G Yu, F Lu BMVC, 2020 | 85 | 2020 |
| Gaze estimation from eye appearance: A head pose-free method via eye image synthesis F Lu, Y Sugano, T Okabe, Y Sato IEEE Transactions on Image Processing 24 (11), 3680-3693, 2015 | 79 | 2015 |
| CPGAN: Content-Parsing Generative Adversarial Networks for Text-to-Image Synthesis J Liang, W Pei, F Lu European Conference on Computer Vision, 491-508, 2020 | 77 | 2020 |
Yunfei LiuInternational Digital Economy Academy (IDEA)Verified email at buaa.edu.cn
