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Qi She (佘琪)
Qi She (佘琪)
其他姓名She Qi, 佘琪, Qi She
Bytedance
在 princeton.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Generative adversarial networks in computer vision: A survey and taxonomy
Z Wang, Q She, TE Ward
ACM Computing Surveys (CSUR) 54 (2), 1-38, 2021
592*2021
Involution: Inverting the Inherence of Convolution for Visual Recognition
D Li, J Hu, C Wang, X Li, Q She, L Zhu, T Zhang, Q Chen
CVPR 2021, 2021
3122021
NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction
Y Gao, Q She, J Ma, M Zhao, W Liu, AL Yuille
CVPR 2019, 3205-3214, 2019
2682019
Avalanche: an End-to-End Library for Continual Learning
V Lomonaco, L Pellegrini, A Cossu, A Carta, G Graffieti, TL Hayes, ...
CVPR 2021 Continual Learning Workshop, 2021
1672021
ACTION-Net: Multipath Excitation for Action Recognition
Z Wang, Q She, A Smolic
CVPR 2021, 2021
1652021
Mine: Towards Continuous Depth MPI with Nerf for Novel View Synthesis
J Li, Z Feng, Q She, H Ding, C Wang, GH Lee
ICCV 2021, 12578-12588, 2021
1312021
Are we ready for service robots? The OpenLORIS-scene datasets for lifelong SLAM
X Shi, D Li, P Zhao, Q Tian, Y Tian, Q Long, C Zhu, J Song, F Qiao, ...
ICRA 2020, 3139-3145, 2020
1222020
OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep Learning
Q She, F Feng, X Hao, Q Yang, C Lan, V Lomonaco, X Shi, Z Wang, ...
ICRA 2020, 4767-4773, 2020
107*2020
Generative adversarial networks in time series: A survey and taxonomy
E Brophy, Z Wang, Q She, T Ward
arXiv preprint arXiv:2107.11098, 2021
802021
Generative adversarial networks in time series: A systematic literature review
E Brophy, Z Wang, Q She, T Ward
ACM Computing Surveys 55 (10), 1-31, 2023
752023
Stochastic Trajectory Prediction with Social Graph Network
L Zhang, Q She, P Guo
arXiv preprint arXiv:1907.10233, 2019
702019
Learning from Temporal Gradient for Semi-supervised Action Recognition
J Xiao, L Jing, L Zhang, J He, Q She, Z Zhou, A Yuille, Y Li
CVPR 2022, 2022
502022
CVPR 2020 continual learning in computer vision competition: Approaches, results, current challenges and future directions
V Lomonaco, L Pellegrini, P Rodriguez, M Caccia, Q She, Y Chen, ...
Artificial Intelligence, 2022, 2022
422022
Challenges in task incremental learning for assistive robotics
F Feng, RHM Chan, X Shi, Y Zhang, Q She
IEEE Access 8, 3434-3441, 2019
422019
On Learning Contrastive Representations for Learning with Noisy Labels
L Yi, S Liu, Q She, AI McLeod, B Wang
CVPR 2022, 2022
402022
Neural dynamics discovery via gaussian process recurrent neural networks
Q She, A Wu
Uncertainty in Artificial Intelligence (UAI), 454-464, 2020
382020
Learning the Superpixel in a Non-iterative and Lifelong Manner
L Zhu, Q She, B Zhang, Y Lu, Z Lu, D Li, J Hu
CVPR 2021, 2021
322021
Weakly Supervised Object Localization as Domain Adaption
L Zhu, Q She, Q Chen, Y You, B Wang, Y Lu
CVPR 2022, 2022
272022
Evaluating the small-world-ness of a sampled network: Functional connectivity of entorhinal-hippocampal circuitry
Q She, G Chen, RHM Chan
Nature Scientific Reports 6, 21468, 2016
262016
Unifying Nonlocal Blocks for Neural Networks
L Zhu, Q She, D Li, Y Lu, X Kang, J Hu, C Wang
ICCV 2021, 2021
242021
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