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 | 783 | 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 | 336 | 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 | 144 | 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 | 135 | 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 | 76 | 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 | 75 | 2020 |
Poly kernel inception network for remote sensing detection X Cai, Q Lai, Y Wang, W Wang, Z Sun, Y Yao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 54 | 2024 |
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 | 26 | 2021 |
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 | 23 | 2019 |
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 | 20 | 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 | 17 | 2022 |
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 | 17 | 2022 |
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 | 14 | 2020 |
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 | 10 | 2023 |
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 | 9 | 2021 |
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 | 8 | 2022 |
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 | 7 | 2023 |
BIFRNet: a brain-inspired feature restoration DNN for partially occluded image recognition J Zhang, L Cao, Q Lai, B Li, Y Qin Proceedings of the AAAI Conference on Artificial Intelligence 37 (12), 15296 …, 2023 | 6 | 2023 |
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 | 6 | 2019 |
Evaluating text-to-image generative models: An empirical study on human image synthesis M Chen, Y Liu, J Yi, C Xu, Q Lai, H Wang, TY Ho, Q Xu arXiv preprint arXiv:2403.05125, 2024 | 5 | 2024 |