| Recent Advances in Convolutional Neural Networks J Gu, Z Wang, J Kuen, L Ma, A Shahroudy, B Shuai, T Liu, X Wang, ... Pattern Recognition 77, 354-377, 2018 | 3160 | 2018 |
| Dual attention matching network for context-aware feature sequence based person re-identification J Si, H Zhang, CG Li, J Kuen, X Kong, AC Kot, G Wang Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 417 | 2018 |
| Recurrent Attentional Networks for Saliency Detection J Kuen, Z Wang, G Wang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 259 | 2016 |
| Motion-guided cascaded refinement network for video object segmentation P Hu, G Wang, X Kong, J Kuen, YP Tan Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 84 | 2018 |
| Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle J Kuen, KM Lim, CP Lee Pattern Recognition 48 (10), 2964-2982, 2015 | 55 | 2015 |
| Multimodal Contrastive Training for Visual Representation Learning X Yuan, Z Lin, J Kuen, J Zhang, Y Wang, M Maire, A Kale, B Faieta Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 45 | 2021 |
| SelfDoc: Self-Supervised Document Representation Learning P Li, J Gu, J Kuen, VI Morariu, H Zhao, R Jain, V Manjunatha, H Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 23 | 2021 |
| DelugeNets: Deep Networks with Efficient and Flexible Cross-layer Information Inflows J Kuen, X Kong, G Wang, YP Tan Computer Vision Workshop (ICCVW), 2017 IEEE International Conference on, 958-966, 2017 | 22* | 2017 |
| Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks J Kuen, X Kong, Z Lin, G Wang, J Yin, S See, YP Tan Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 20* | 2018 |
| Multi-Scale Aligned Distillation for Low-Resolution Detection L Qi, J Kuen, J Gu, Z Lin, Y Wang, Y Chen, Y Li, J Jia Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 18 | 2021 |
| Utilizing a deep neural network-based model to identify visually similar digital images based on user-selected visual attributes Z Lin, S Xiaohui, M Ling, J Zhang, J Kuen, B Butterfield US Patent 10,628,708, 2020 | 16 | 2020 |
| Self-supervised relationship probing J Gu, J Kuen, S Joty, J Cai, V Morariu, H Zhao, T Sun Advances in Neural Information Processing Systems 33, 1841-1853, 2020 | 14 | 2020 |
| Scaling object detection by transferring classification weights J Kuen, F Perazzi, Z Lin, J Zhang, YP Tan Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 13 | 2019 |
| Open-world entity segmentation L Qi, J Kuen, Y Wang, J Gu, H Zhao, Z Lin, P Torr, J Jia arXiv preprint arXiv:2107.14228, 2021 | 11 | 2021 |
| Object Detection In Images Z Lin, S Xiaohui, M Ling, J Zhang, JWY Kuen US Patent App. 16/189,805, 2020 | 9 | 2020 |
| Unidoc: Unified pretraining framework for document understanding J Gu, J Kuen, VI Morariu, H Zhao, R Jain, N Barmpalios, A Nenkova, ... Advances in Neural Information Processing Systems 34, 39-50, 2021 | 8 | 2021 |
| Robust training of large-scale object detectors with a noisy dataset Z Lin, M Ling, J Zhang, J Kuen, F Perazzi, B Butterfield, B Faieta US Patent 11,126,890, 2021 | 6 | 2021 |
| Open-vocabulary instance segmentation via robust cross-modal pseudo-labeling D Huynh, J Kuen, Z Lin, J Gu, E Elhamifar Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 5 | 2022 |
| Casp: Class-agnostic semi-supervised pretraining for detection and segmentation L Qi, J Kuen, Z Lin, J Gu, F Rao, D Li, W Guo, Z Wen, J Jia arXiv preprint arXiv:2112.04966, 2021 | 3 | 2021 |
| High Quality Segmentation for Ultra High-resolution Images T Shen, Y Zhang, L Qi, J Kuen, X Xie, J Wu, Z Lin, J Jia Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 1 | 2022 |
Jiuxiang GuResearch Scientist, Adobe ResearchVerified email at adobe.com
