Detecting anomalous events in videos by learning deep representations of appearance and motion D Xu, Y Yan, E Ricci, N Sebe Computer Vision and Image Understanding (CVIU), 2017 | 1094* | 2017 |
Pad-net: Multi-tasks guided prediction-and-distillation network for simultaneous depth estimation and scene parsing D Xu, W Ouyang, X Wang, N Sebe IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2018 | 559 | 2018 |
Multi-scale continuous crfs as sequential deep networks for monocular depth estimation D Xu, E Ricci, W Ouyang, X Wang, N Sebe IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 545 | 2017 |
Multi-channel attention selection gan with cascaded semantic guidance for cross-view image translation H Tang, D Xu, N Sebe, Y Wang, JJ Corso, Y Yan IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 426 | 2019 |
Structured attention guided convolutional neural fields for monocular depth estimation D Xu, W Wang, H Tang, H Liu, N Sebe, E Ricci IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2018 | 387 | 2018 |
Group consistent similarity learning via deep CRFs for person re-identification D Chen, D Xu, H Li, N Sebe, X Wang IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2018 | 270 | 2018 |
Attentiongan: Unpaired image-to-image translation using attention-guided generative adversarial networks H Tang, H Liu, D Xu, PHS Torr, N Sebe IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 | 261 | 2021 |
Learning cross-modal deep representations for robust pedestrian detection D Xu, W Ouyang, E Ricci, X Wang, N Sebe IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 253 | 2017 |
Delving into localization errors for monocular 3D object detection X Ma, Y Zhang, D Xu, D Zhou, S Yi, H Li, W Ouyang IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 244 | 2021 |
Multi-class token transformer for weakly supervised semantic segmentation L Xu, W Ouyang, M Bennamoun, F Boussaid, D Xu IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 233 | 2022 |
Unsupervised adversarial depth estimation using cycled generative networks A Pilzer, D Xu, M Puscas, E Ricci, N Sebe IEEE International Conference on 3D Vision (3DV Oral), 2018 | 212 | 2018 |
Transformer-based attention networks for continuous pixel-wise prediction G Yang, H Tang, M Ding, D Xu, N Sebe, E Ricci IEEE International Conference on Computer Vision (ICCV), 2021 | 205 | 2021 |
Local class-specific and global image-level generative adversarial networks for semantic-guided scene generation H Tang, D Xu, Y Yan, PHS Torr, N Sebe IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 186 | 2020 |
Leveraging auxiliary tasks with affinity learning for weakly supervised semantic segmentation L Xu, W Ouyang, M Bennamoun, F Boussaid, F Sohel, D Xu IEEE International Conference on Computer Vision (ICCV), 2021 | 167 | 2021 |
Depth-aware generative adversarial network for talking head video generation FT Hong, L Zhang, L Shen, D Xu IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 165 | 2022 |
Neural information retrieval: At the end of the early years KD Onal, Y Zhang, IS Altingovde, MM Rahman, P Karagoz, A Braylan, ... Springer Information Retrieval 21 (2), 111-182, 2018 | 159 | 2018 |
Attention-guided generative adversarial networks for unsupervised image-to-image translation H Tang, D Xu, N Sebe, Y Yan arXiv preprint arXiv:1903.12296, 2019 | 157 | 2019 |
Dynamic graph message passing networks L Zhang, D Xu, A Arnab, PHS Torr IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 150 | 2020 |
Learning deep structured multi-scale features using attention-gated crfs for contour prediction D Xu, W Ouyang, X Alameda-Pineda, E Ricci, X Wang, N Sebe Advances in Neural Information Processing Systems (NeurIPS), 2017 | 140 | 2017 |
DetCLIP: Dictionary-enriched visual-concept paralleled pre-training for open-world detection L Yao, J Han, Y Wen, X Liang, D Xu, W Zhang, Z Li, C Xu, H Xu Advances in Neural Information Processing Systems (NeurIPS), 2022 | 132 | 2022 |