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Junyu Gao
Junyu Gao
Xidian University
Verified email at mail.nwpu.edu.cn - Homepage
Title
Cited by
Cited by
Year
Learning from synthetic data for crowd counting in the wild
Q Wang, J Gao, W Lin, Y Yuan
Proceedings of the IEEE/CVF Conference on computer vision and pattern …, 2019
3232019
Embedding structured contour and location prior in siamesed fully convolutional networks for road detection
J Gao, Q Wang, Y Yuan
Robotics and Automation (ICRA), 2017 IEEE International Conference on, 219-224, 2017
2232017
NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization
Q Wang, J Gao, W Lin, X Li
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
1552020
Weakly supervised adversarial domain adaptation for semantic segmentation in urban scenes
Q Wang, J Gao, X Li
IEEE Transactions on Image Processing 28 (9), 4376-4386, 2019
1392019
A joint convolutional neural networks and context transfer for street scenes labeling
Q Wang, J Gao, Y Yuan
IEEE Transactions on Intelligent Transportation Systems 19 (5), 1457-1470, 2018
1312018
Pcc net: Perspective crowd counting via spatial convolutional network
J Gao, Q Wang, X Li
IEEE Transactions on Circuits and Systems for Video Technology 30 (10), 3486 …, 2019
1172019
SCAR: Spatial-/channel-wise attention regression networks for crowd counting
J Gao, Q Wang, Y Yuan
Neurocomputing 363, 1-8, 2019
1092019
Cnn-based density estimation and crowd counting: A survey
G Gao, J Gao, Q Liu, Q Wang, Y Wang
arXiv preprint arXiv:2003.12783, 2020
792020
C^3 Framework: An Open-source PyTorch Code for Crowd Counting
J Gao, W Lin, B Zhao, D Wang, C Gao, J Wen
arXiv preprint arXiv:1907.02724, 2019
592019
Pixel-wise crowd understanding via synthetic data
Q Wang, J Gao, W Lin, Y Yuan
International Journal of Computer Vision 129 (1), 225-245, 2021
482021
Feature-Aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance
J Gao, Y Yuan, Q Wang
IEEE Transactions on Cybernetics, 2020
32*2020
Neuron linear transformation: Modeling the domain shift for crowd counting
Q Wang, T Han, J Gao, Y Yuan
IEEE Transactions on Neural Networks and Learning Systems, 2021
312021
Domain-Adaptive Crowd Counting via High-Quality Image Translation and Density Reconstruction
J Gao, T Han, Y Yuan, Q Wang
IEEE transactions on neural networks and learning systems, 2021
29*2021
Multitask attention network for lane detection and fitting
Q Wang, T Han, Z Qin, J Gao, X Li
IEEE transactions on neural networks and learning systems, 2020
292020
Focus on semantic consistency for cross-domain crowd understanding
T Han, J Gao, Y Yuan, Q Wang
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
232020
Ambient sound helps: Audiovisual crowd counting in extreme conditions
D Hu, L Mou, Q Wang, J Gao, Y Hua, D Dou, XX Zhu
arXiv preprint arXiv:2005.07097, 2020
152020
Unsupervised Semantic Aggregation and Deformable Template Matching for Semi-Supervised Learning
T Han, J Gao, Y Yuan, Q Wang
Advances in Neural Information Processing Systems 33, 2020
122020
Learning to detect anomaly events in crowd scenes from synthetic data
W Lin, J Gao, Q Wang, X Li
Neurocomputing 436, 248-259, 2021
112021
Density-Aware Curriculum Learning for Crowd Counting
Q Wang, W Lin, J Gao, X Li
IEEE Transactions on Cybernetics, 2020
102020
VisDrone-CC2020: The vision meets drone crowd counting challenge results
D Du, L Wen, P Zhu, H Fan, Q Hu, H Ling, M Shah, J Pan, A Al-Ali, ...
European Conference on Computer Vision, 675-691, 2020
72020
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