| Salient object detection in the deep learning era: An in-depth survey W Wang, Q Lai, H Fu, J Shen, H Ling, R Yang IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (6), 3239-3259, 2021 | 677 | 2021 |
| Scinet: Time series modeling and forecasting with sample convolution and interaction M Liu, A Zeng, M Chen, Z Xu, Q Lai, L Ma, Q Xu Advances in Neural Information Processing Systems 35, 5816-5828, 2022 | 136 | 2022 |
| Video saliency prediction using spatiotemporal residual attentive networks Q Lai, W Wang, H Sun, J Shen IEEE Transactions on Image Processing 29, 1113-1126, 2019 | 130 | 2019 |
| Time series is a special sequence: Forecasting with sample convolution and interaction M Liu, A Zeng, Z Xu, Q Lai, Q Xu arXiv preprint arXiv:2106.09305 1 (9), 2021 | 103 | 2021 |
| DeepFuse: An IMU-aware network for real-time 3D human pose estimation from multi-view image F Huang, A Zeng, M Liu, Q Lai, Q Xu Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020 | 61 | 2020 |
| Understanding more about human and machine attention in deep neural networks Q Lai, S Khan, Y Nie, H Sun, J Shen, L Shao IEEE Transactions on Multimedia 23, 2086-2099, 2020 | 54 | 2020 |
| Multi-view video synopsis via simultaneous object-shifting and view-switching optimization Z Zhang, Y Nie, H Sun, Q Zhang, Q Lai, G Li, M Xiao IEEE transactions on image processing 29, 971-985, 2019 | 20 | 2019 |
| Testrank: Bringing order into unlabeled test instances for deep learning tasks Y Li, M Li, Q Lai, Y Liu, Q Xu Advances in Neural Information Processing Systems 34, 20874-20886, 2021 | 18 | 2021 |
| Weakly supervised visual saliency prediction Q Lai, T Zhou, S Khan, H Sun, J Shen, L Shao IEEE Transactions on Image Processing 31, 3111-3124, 2022 | 14 | 2022 |
| T-wavenet: A tree-structured wavelet neural network for time series signal analysis LIU Minhao, A Zeng, LAI Qiuxia, R Gao, M Li, J Qin, Q Xu International Conference on Learning Representations, 2021 | 12 | 2021 |
| Video super-resolution via pre-frame constrained and deep-feature enhanced sparse reconstruction Q Lai, Y Nie, H Sun, Q Xu, Z Zhang, M Xiao Pattern Recognition 100, 107139, 2020 | 12 | 2020 |
| What you see is not what the network infers: Detecting adversarial examples based on semantic contradiction Y Yang, R Gao, Y Li, Q Lai, Q Xu arXiv preprint arXiv:2201.09650, 2022 | 11 | 2022 |
| Human vs. machine attention in neural networks: A comparative study Q Lai, W Wang, S Khan, J Shen, H Sun, L Shao arXiv preprint arXiv:1906.08764 3 (8), 2019 | 7 | 2019 |
| Deepsat: An eda-driven learning framework for sat M Li, Z Shi, Q Lai, S Khan, S Cai, Q Xu arXiv preprint arXiv:2205.13745, 2022 | 6 | 2022 |
| Human\textit {vs} machine attention in neural networks: A comparative study Q Lai, W Wang, S Khan, J Shen, H Sun, L Shao arXiv preprint arXiv:1906.08764, 2019 | 5 | 2019 |
| Information bottleneck approach to spatial attention learning Q Lai, Y Li, A Zeng, M Liu, H Sun, Q Xu arXiv preprint arXiv:2108.03418, 2021 | 4 | 2021 |
| On EDA-Driven Learning for SAT Solving M Li, Z Shi, Q Lai, S Khan, S Cai, Q Xu 2023 60th ACM/IEEE Design Automation Conference (DAC), 1-6, 2023 | 3 | 2023 |
| Multi-video object synopsis integrating optimal view switching Z Zhang, Y Nie, H Sun, Q Lai, G Li SIGGRAPH Asia 2017 Technical Briefs, 1-4, 2017 | 3 | 2017 |
| EEG-based visual stimuli classification via reusable LSTM Y Deng, S Ding, W Li, Q Lai, L Cao Biomedical Signal Processing and Control 82, 104588, 2023 | 2 | 2023 |
| T-wavenet: Tree-structured wavelet neural network for sensor-based time series analysis M Liu, A Zeng, Q Lai, Q Xu arXiv preprint arXiv:2012.05456, 2020 | 2 | 2020 |
