フォロー
Qi Tian, Chief Scientist in Artificial Intelligence, Fellow of IEEE/CAAI/CCF, IEAS Academician
Qi Tian, Chief Scientist in Artificial Intelligence, Fellow of IEEE/CAAI/CCF, IEAS Academician
Huawei Cloud
確認したメール アドレス: huawei.com - ホームページ
タイトル
引用先
引用先
Scalable person re-identification: A benchmark
L Zheng, L Shen, L Tian, S Wang, J Wang, Q Tian
Proceedings of the IEEE international conference on computer vision, 1116-1124, 2015
52742015
Ghostnet: More features from cheap operations
K Han, Y Wang, Q Tian, J Guo, C Xu, C Xu
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
37102020
Centernet: Keypoint triplets for object detection
K Duan, S Bai, L Xie, H Qi, Q Huang, Q Tian
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
37022019
Swin-unet: Unet-like pure transformer for medical image segmentation
H Cao, Y Wang, J Chen, D Jiang, X Zhang, Q Tian, M Wang
European conference on computer vision, 205-218, 2022
34322022
Beyond part models: Person retrieval with refined part pooling (and a strong convolutional baseline)
Y Sun, L Zheng, Y Yang, Q Tian, S Wang
Proceedings of the European conference on computer vision (ECCV), 480-496, 2018
28392018
Person transfer gan to bridge domain gap for person re-identification
L Wei, S Zhang, W Gao, Q Tian
Proceedings of the IEEE conference on computer vision and pattern …, 2018
21332018
Actional-structural graph convolutional networks for skeleton-based action recognition
M Li, S Chen, X Chen, Y Zhang, Y Wang, Q Tian
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
12802019
Mars: A video benchmark for large-scale person re-identification
L Zheng, Z Bie, Y Sun, J Wang, C Su, S Wang, Q Tian
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
12092016
Deep modular co-attention networks for visual question answering
Z Yu, J Yu, Y Cui, D Tao, Q Tian
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
10132019
Pose-driven deep convolutional model for person re-identification
C Su, J Li, S Zhang, J Xing, W Gao, Q Tian
Proceedings of the IEEE international conference on computer vision, 3960-3969, 2017
9792017
Person re-identification in the wild
L Zheng, H Zhang, S Sun, M Chandraker, Y Yang, Q Tian
Proceedings of the IEEE conference on computer vision and pattern …, 2017
9482017
Accurate medium-range global weather forecasting with 3D neural networks
K Bi, L Xie, H Zhang, X Chen, X Gu, Q Tian
Nature 619 (7970), 533-538, 2023
930*2023
Pc-darts: Partial channel connections for memory-efficient architecture search
Y Xu, L Xie, X Zhang, X Chen, GJ Qi, Q Tian, H Xiong
arXiv preprint arXiv:1907.05737, 2019
9072019
SIFT meets CNN: A decade survey of instance retrieval
L Zheng, Y Yang, Q Tian
IEEE transactions on pattern analysis and machine intelligence 40 (5), 1224-1244, 2017
8692017
The unmanned aerial vehicle benchmark: Object detection and tracking
D Du, Y Qi, H Yu, Y Yang, K Duan, G Li, W Zhang, Q Huang, Q Tian
Proceedings of the European conference on computer vision (ECCV), 370-386, 2018
8382018
Progressive differentiable architecture search: Bridging the depth gap between search and evaluation
X Chen, L Xie, J Wu, Q Tian
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
7902019
Conformer: Local features coupling global representations for visual recognition
Z Peng, W Huang, S Gu, L Xie, Y Wang, J Jiao, Q Ye
Proceedings of the IEEE/CVF international conference on computer vision, 367-376, 2021
7492021
Deep representation learning with part loss for person re-identification
H Yao, S Zhang, R Hong, Y Zhang, C Xu, Q Tian
IEEE Transactions on Image Processing 28 (6), 2860-2871, 2019
5012019
Novel visual and statistical image features for microblogs news verification
Z Jin, J Cao, Y Zhang, J Zhou, Q Tian
IEEE transactions on multimedia 19 (3), 598-608, 2016
4922016
Multi-cue correlation filters for robust visual tracking
N Wang, W Zhou, Q Tian, R Hong, M Wang, H Li
Proceedings of the IEEE conference on computer vision and pattern …, 2018
4912018
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