Towards understanding regularization in batch normalization P Luo, X Wang, W Shao, Z Peng arXiv preprint arXiv:1809.00846, 2018 | 251 | 2018 |
Differentiable learning-to-normalize via switchable normalization P Luo, J Ren, Z Peng, R Zhang, J Li arXiv preprint arXiv:1806.10779, 2018 | 237 | 2018 |
Switchable normalization for learning-to-normalize deep representation P Luo, R Zhang, J Ren, Z Peng, J Li IEEE transactions on pattern analysis and machine intelligence 43 (2), 712-728, 2019 | 80 | 2019 |
Aim 2020 challenge on learned image signal processing pipeline A Ignatov, R Timofte, Z Zhang, M Liu, H Wang, W Zuo, J Zhang, R Zhang, ... Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 61 | 2020 |
Differentiable learning-to-group channels via groupable convolutional neural networks Z Zhang, J Li, W Shao, Z Peng, R Zhang, X Wang, P Luo Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 41 | 2019 |
Differentiable dynamic normalization for learning deep representation P Luo, P Zhanglin, S Wenqi, Z Ruimao, R Jiamin, W Lingyun International Conference on Machine Learning, 4203-4211, 2019 | 26 | 2019 |
Facial age estimation by using stacked feature composition and selection Y Li, Z Peng, D Liang, H Chang, Z Cai The Visual Computer 32, 1525-1536, 2016 | 24 | 2016 |
Deep boosting: joint feature selection and analysis dictionary learning in hierarchy Z Peng, Y Li, Z Cai, L Lin Neurocomputing 178, 36-45, 2016 | 22 | 2016 |
Progressively diffused networks for semantic visual parsing R Zhang, W Yang, Z Peng, P Wei, X Wang, L Lin Pattern Recognition 90, 78-86, 2019 | 19* | 2019 |
Exemplar normalization for learning deep representation R Zhang, Z Peng, L Wu, Z Li, P Luo Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 18 | 2020 |
Geometric scene parsing with hierarchical lstm Z Peng, R Zhang, X Liang, X Liu, L Lin arXiv preprint arXiv:1604.01931, 2016 | 17 | 2016 |
Multi-stage spatio-temporal aggregation transformer for video person re-identification Z Tang, R Zhang, Z Peng, J Chen, L Lin IEEE Transactions on Multimedia 25, 7917-7929, 2022 | 16 | 2022 |
Do normalization layers in a deep ConvNet really need to be distinct? P Luo, Z Peng, J Ren, R Zhang arXiv preprint arXiv:1811.07727, 2018 | 13 | 2018 |
Deep boosting: Layered feature mining for general image classification Z Peng, L Lin, R Zhang, J Xu 2014 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2014 | 12 | 2014 |
Differentiable learning-to-normalize via switchable normalization. arXiv P Luo, J Ren, Z Peng, R Zhang, J Li arXiv preprint arXiv:1806.10779, 2018 | 7 | 2018 |
Cuimage: a neverending learning platform on a convolutional knowledge graph of billion web images Z Peng, L Wu, J Ren, R Zhang, P Luo 2018 IEEE International Conference on Big Data (Big Data), 1787-1796, 2018 | 6 | 2018 |
Foundation model is efficient multimodal multitask model selector F Meng, W Shao, Z Peng, C Jiang, K Zhang, Y Qiao, P Luo arXiv preprint arXiv:2308.06262, 2023 | 4 | 2023 |
Normalization method and apparatus for deep neural network, and storage media P Luo, L Wu, J Ren, P Zhanglin, R Zhang, W Xinjiang US Patent App. 16/862,304, 2020 | 2 | 2020 |
Community Channel-Net: Efficient channel-wise interactions via community graph topology F Feng, Q Liu, Z Peng, R Zhang, RHM Chan Pattern Recognition 141, 109536, 2023 | 1 | 2023 |
Image normalization processing R Zhang, P Zhanglin, L Wu, P Luo US Patent App. 17/893,797, 2022 | 1 | 2022 |