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Qi Dai
Qi Dai
Microsoft Research
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
SimMIM: A simple framework for masked image modeling
Z Xie, Z Zhang, Y Cao, Y Lin, J Bao, Z Yao, Q Dai, H Hu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
5602022
Trajectory-based modeling of human actions with motion reference points
YG Jiang, Q Dai, X Xue, W Liu, CW Ngo
Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012
2842012
Weakly-supervised action localization by generative attention modeling
B Shi, Q Dai, Y Mu, J Wang
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
1462020
Learning spatial awareness to improve crowd counting
ZQ Cheng, JX Li, Q Dai, X Wu, AG Hauptmann
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
1252019
Self-supervised learning with swin transformers
Z Xie, Y Lin, Z Yao, Z Zhang, Q Dai, Y Cao, H Hu
arXiv preprint arXiv:2105.04553, 2021
1192021
Recurrent tubelet proposal and recognition networks for action detection
D Li, Z Qiu, Q Dai, T Yao, T Mei
Proceedings of the European conference on computer vision (ECCV), 303-318, 2018
1132018
Deep incremental hashing network for efficient image retrieval
D Wu, Q Dai, J Liu, B Li, W Wang
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
1032019
On the connection between local attention and dynamic depth-wise convolution
Q Han, Z Fan, Q Dai, L Sun, MM Cheng, J Liu, J Wang
International Conference on Learning Representations, 2022
88*2022
Fudan-Huawei at MediaEval 2015: Detecting Violent Scenes and Affective Impact in Movies with Deep Learning.
Q Dai, RW Zhao, Z Wu, X Wang, Z Gu, W Wu, YG Jiang
MediaEval 1436, 2015
882015
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
B Shi, D Zhang, Q Dai, Z Zhu, Y Mu, J Wang
Proceedings of the 37th International Conference on Machine Learning, 8828--8839, 2020
802020
Human action recognition in unconstrained videos by explicit motion modeling
YG Jiang, Q Dai, W Liu, X Xue, CW Ngo
IEEE Transactions on Image Processing 24 (11), 3781-3795, 2015
792015
Improving the Learning of Multi-column Convolutional Neural Network for Crowd Counting
ZQ Cheng, JX Li, Q Dai, X Wu, JY He, A Hauptmann
Proceedings of the 27th ACM International Conference on Multimedia, 1897-1906, 2019
682019
Super fast event recognition in internet videos
YG Jiang, Q Dai, T Mei, Y Rui, SF Chang
IEEE Transactions on Multimedia 17 (8), 1174-1186, 2015
682015
Fast semantic diffusion for large-scale context-based image and video annotation
YG Jiang, Q Dai, J Wang, CW Ngo, X Xue, SF Chang
IEEE Transactions on Image Processing 21 (6), 3080-3091, 2012
592012
Decoupling Localization and Classification in Single Shot Temporal Action Detection
Y Huang, Q Dai, Y Lu
2019 IEEE International Conference on Multimedia and Expo (ICME), 2019
442019
Binary optimized hashing
Q Dai, J Li, J Wang, YG Jiang
Proceedings of the 24th ACM international conference on Multimedia, 1247-1256, 2016
382016
Rethinking spatial invariance of convolutional networks for object counting
ZQ Cheng, Q Dai, H Li, J Song, X Wu, AG Hauptmann
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
362022
Beauty is here: evaluating aesthetics in videos using multimodal features and free training data
Y Wang, Q Dai, R Feng, YG Jiang
Proceedings of the 21st ACM international conference on Multimedia, 369-372, 2013
322013
Fudan-NJUST at MediaEval 2014: Violent Scenes Detection Using Deep Neural Networks.
Q Dai, Z Wu, YG Jiang, X Xue, J Tang
MediaEval, 2014
282014
Fudan at MediaEval 2013: Violent Scenes Detection Using Motion Features and Part-Level Attributes.
Q Dai, J Tu, Z Shi, YG Jiang, X Xue
MediaEval, 2013
252013
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Articles 1–20