| Path aggregation network for instance segmentation S Liu, L Qi, H Qin, J Shi, J Jia Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 788 | 2018 |
| Faster R-CNN for marine organisms detection and recognition using data augmentation H Huang, H Zhou, X Yang, L Zhang, L Qi, AY Zang Neurocomputing 337, 372-384, 2019 | 36 | 2019 |
| Amodal instance segmentation with kins dataset L Qi, L Jiang, S Liu, X Shen, J Jia Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 28 | 2019 |
| A novel biologically inspired visual cognition model: automatic extraction of semantics, formation of integrated concepts, and reselection features for ambiguity P Yin, H Qiao, W Wu, L Qi, Y Li, S Zhong, B Zhang IEEE Transactions on Cognitive and Developmental Systems 10 (2), 420-431, 2017 | 11 | 2017 |
| Sequential context encoding for duplicate removal L Qi, S Liu, J Shi, J Jia arXiv preprint arXiv:1810.08770, 2018 | 9 | 2018 |
| MuCAN: Multi-correspondence Aggregation Network for Video Super-Resolution W Li, X Tao, T Guo, L Qi, J Lu, J Jia European Conference on Computer Vision, 335-351, 2020 | 5 | 2020 |
| Pointins: Point-based instance segmentation L Qi, X Zhang, Y Chen, Y Chen, J Sun, J Jia arXiv preprint arXiv:2003.06148, 2020 | 4 | 2020 |
| Faster R-CNN for marine organism detection and recognition using data augmentation H Zhou, H Huang, X Yang, L Zhang, L Qi Proceedings of the International Conference on Video and Image Processing, 56-62, 2017 | 3 | 2017 |
| LSUN’17: insatnce segmentation task, UCenter winner team S Liu, L Qi, H Qin, J Shi, J Jia Hawaii Convention Center, 2017 | 3 | 2017 |
| RGB-D Co-attention Network for Semantic Segmentation H Zhou, L Qi, Z Wan, H Huang, X Yang Proceedings of the Asian Conference on Computer Vision, 2020 | 1 | 2020 |
| A novel biologically mechanism-based visual cognition model--automatic extraction of semantics, formation of integrated concepts and re-selection features for ambiguity P Yin, H Qiao, W Wu, L Qi, YL Li, S Zhong, B Zhang arXiv preprint arXiv:1603.07886, 2016 | 1 | 2016 |
| Scale-aware Automatic Augmentation for Object Detection Y Chen, Y Li, T Kong, L Qi, R Chu, L Li, J Jia arXiv preprint arXiv:2103.17220, 2021 | | 2021 |
| Best-Buddy GANs for Highly Detailed Image Super-Resolution W Li, K Zhou, L Qi, L Lu, N Jiang, J Lu, J Jia arXiv preprint arXiv:2103.15295, 2021 | | 2021 |
| Instance segmentation methods and apparatuses, electronic devices, programs, and media S Liu, L Qi, QIN Haifang, SHI Jianping, J Jia US Patent App. 16/729,423, 2020 | | 2020 |
| LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-resolution and Beyond W Li, K Zhou, L Qi, N Jiang, J Lu, J Jia Advances in Neural Information Processing Systems 33, 2020 | | 2020 |
| NFLB dropout: Improve generalization ability by dropping out the best-A biologically inspired adaptive dropout method for unsupervised learning P Yin, L Qi, X Xi, B Zhang, H Qiao 2016 International Joint Conference on Neural Networks (IJCNN), 1180-1186, 2016 | | 2016 |
| Transfer classification for distinct manifestations with shared information L Qi, P Yin, X Huang, K Chen, H Qiao 2016 12th World Congress on Intelligent Control and Automation (WCICA), 1234 …, 2016 | | 2016 |
| Multi-Scale Aligned Distillation for Low-Resolution Detection L Qi, J Kuen, J Gu, Z Lin, Y Wang, Y Chen, Y Li, J Jia | | |
| Supplementary Material of LAPAR W Li, K Zhou, L Qi, N Jiang, J Lu, J Jia | | |
