| DenseASPP for semantic segmentation in street scenes M Yang, K Yu, C Zhang, Z Li, K Yang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 1638 | 2018 |
| The application of two-level attention models in deep convolutional neural network for fine-grained image classification T Xiao, Y Xu, K Yang, J Zhang, Y Peng, Z Zhang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 1057 | 2015 |
| Semantic Flow for Fast and Accurate Scene Parsing X Li, A You, Z Zhu, H Zhao, M Yang, K Yang, S Tan, Y Tong Proceedings of the European Conference on Computer Vision, 2020 | 434 | 2020 |
| Hard-aware deeply cascaded embedding Y Yuan, K Yang, C Zhang Proceedings of the IEEE International Conference on Computer Vision, 814-823, 2017 | 356 | 2017 |
| Error-driven incremental learning in deep convolutional neural network for large-scale image classification T Xiao, J Zhang, K Yang, Y Peng, Z Zhang Proceedings of the 22nd ACM international conference on Multimedia, 177-186, 2014 | 326 | 2014 |
| Towards a relevant and diverse search of social images M Wang, K Yang, XS Hua, HJ Zhang IEEE transactions on multimedia 12 (8), 829-842, 2010 | 272 | 2010 |
| Feature-metric loss for self-supervised learning of depth and egomotion C Shu, K Yu, Z Duan, K Yang European Conference on Computer Vision, 572-588, 2020 | 261 | 2020 |
| Dual graph convolutional network for semantic segmentation L Zhang, X Li, A Arnab, K Yang, Y Tong, PHS Torr arXiv preprint arXiv:1909.06121, 2019 | 251 | 2019 |
| GFF: Gated Fully Fusion for Semantic Segmentation X Li, H Zhao, L Han, Y Tong, K Yang Proceedings of the AAAI Conference on Artificial Intelligence, 2020 | 232 | 2020 |
| Adaptive unimodal cost volume filtering for deep stereo matching Y Zhang, Y Chen, X Bai, S Yu, K Yu, Z Li, K Yang Proceedings of the AAAI Conference on Artificial Intelligence 34 (07), 12926 …, 2020 | 191 | 2020 |
| Visualizing and comparing AlexNet and VGG using deconvolutional layers W Yu, K Yang, Y Bai, T Xiao, H Yao, Y Rui Proceedings of the 33 rd International Conference on Machine Learning, 2016 | 183 | 2016 |
| Scale-invariant convolutional neural networks Y Xu, T Xiao, J Zhang, K Yang, Z Zhang arXiv preprint arXiv:1411.6369, 2014 | 178 | 2014 |
| Exploiting the complementary strengths of multi-layer CNN features for image retrieval W Yu, K Yang, H Yao, X Sun, P Xu Neurocomputing 237, 235-241, 2017 | 145 | 2017 |
| You lead, we exceed: Labor-free video concept learning by jointly exploiting web videos and images C Gan, T Yao, K Yang, Y Yang, T Mei Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 133 | 2016 |
| Query-dependent aesthetic model with deep learning for photo quality assessment X Tian, Z Dong, K Yang, T Mei IEEE Transactions on Multimedia 17 (11), 2035-2048, 2015 | 112 | 2015 |
| Visualizing and comparing convolutional neural networks W Yu, K Yang, Y Bai, H Yao, Y Rui arXiv preprint arXiv:1412.6631, 2014 | 78 | 2014 |
| Global aggregation then local distribution in fully convolutional networks X Li, L Zhang, A You, M Yang, K Yang, Y Tong arXiv preprint arXiv:1909.07229, 2019 | 75 | 2019 |
| Bag-of-words based deep neural network for image retrieval Y Bai, W Yu, T Xiao, C Xu, K Yang, WY Ma, T Zhao Proceedings of the 22nd ACM international conference on Multimedia, 229-232, 2014 | 55 | 2014 |
| Hierarchical semantic image matching using CNN feature pyramid W Yu, X Sun, K Yang, Y Rui, H Yao Computer Vision and Image Understanding 169, 40-51, 2018 | 50 | 2018 |
| Tag Tagging: Towards More Descriptive Keywords of Image Content K Yang, X Hua, M Wang, H Zhang IEEE Transactions on Multimedia 13 (4), 662-673, 2011 | 48 | 2011 |
Xiangtai LiResearch Scientist, TikTok, SG; Nanyang Technological UniversityVerified email at pku.edu.cn
