Co-scale conv-attentional image transformers W Xu, Y Xu, T Chang, Z Tu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 330 | 2021 |
Pose recognition with cascade transformers K Li, S Wang, X Zhang, Y Xu, W Xu, Z Tu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 200 | 2021 |
Guided variational autoencoder for disentanglement learning Z Ding, Y Xu, W Xu, G Parmar, Y Yang, M Welling, Z Tu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 109 | 2020 |
Line segment detection using transformers without edges Y Xu, W Xu, D Cheung, Z Tu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 105 | 2021 |
Attentional constellation nets for few-shot learning W Xu, Y Xu, H Wang, Z Tu International conference on learning representations, 2021 | 99 | 2021 |
Wasserstein introspective neural networks K Lee, W Xu, F Fan, Z Tu Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 57 | 2018 |
Instance segmentation with mask-supervised polygonal boundary transformers J Lazarow, W Xu, Z Tu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 27 | 2022 |
3D volumetric modeling with introspective neural networks W Huang, B Lai, W Xu, Z Tu Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 8481-8488, 2019 | 20 | 2019 |
Convolutions and self-attention: Re-interpreting relative positions in pre-trained language models TA Chang, Y Xu, W Xu, Z Tu ACL 2021, 2021 | 14 | 2021 |
Geometry-Aware End-to-End Skeleton Detection. W Xu, G Parmar, Z Tu BMVC 2 (3), 7, 2019 | 12 | 2019 |
Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks B Xiao, H Wu, W Xu, X Dai, H Hu, Y Lu, M Zeng, C Liu, L Yuan CVPR 2024, 2023 | 8 | 2023 |
Exploring Visual Structures in Deep Representation Learning W Xu University of California, San Diego, 2022 | | 2022 |