Folgen
Ziyan Wu
Ziyan Wu
UII America, Inc.
Bestätigte E-Mail-Adresse bei rpi.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Review of artificial intelligence techniques in imaging data acquisition, segmentation, and diagnosis for COVID-19
F Shi, J Wang, J Shi, Z Wu, Q Wang, Z Tang, K He, Y Shi, D Shen
IEEE reviews in biomedical engineering 14, 4-15, 2020
14392020
Tell Me Where to Look: Guided Attention Inference Network
K Li, Z Wu, KC Peng, J Ernst, Y Fu
Computer Vision and Pattern Recognition (CVPR), 2018 IEEE Conference on, 2018
5902018
Counterfactual Visual Explanations
Y Goyal, Z Wu, J Ernst, D Batra, D Parikh, S Lee
International Conference on Machine Learning, 2019
5272019
Learning without Memorizing
P Dhar, RV Singh, KC Peng, Z Wu, R Chellappa
Computer Vision and Pattern Recognition (CVPR), 2019 IEEE Conference on, 2019
4782019
Re-Identification with Consistent Attentive Siamese Networks
M Zheng, S Karanam, Z Wu, RJ Radke
Computer Vision and Pattern Recognition (CVPR), 2019 IEEE Conference on, 2019
2922019
A systematic evaluation and benchmark for person re-identification: Features, metrics, and datasets
M Gou, Z Wu, A Rates-Borras, O Camps, RJ Radke
IEEE transactions on pattern analysis and machine intelligence 41 (3), 523-536, 2018
2682018
Towards Visually Explaining Variational Autoencoders
W Liu, R Li, M Zheng, S Karanam, Z Wu, B Bhanu, RJ Radke, O Camps
Computer Vision and Pattern Recognition (CVPR), 2020 IEEE Conference on, 2020
2202020
Viewpoint Invariant Human Re-identification in Camera Networks Using Pose Priors and Subject-Discriminative Features
Z Wu, Y Li, RJ Radke
IEEE Transactions on Pattern Analysis and Machine Intelligence 37 (5), 1095 …, 2015
1532015
Weakly Supervised Summarization of Web Videos
R Panda, A Das, Z Wu, J Ernst, AK Roy-Chowdhury
Proceedings of the IEEE International Conference on Computer Vision, 3657-3666, 2017
1012017
Hierarchical kinematic human mesh recovery
G Georgakis, R Li, S Karanam, T Chen, J Košecká, Z Wu
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
972020
Zero-shot deep domain adaptation
KC Peng, Z Wu, J Ernst
European Conference on Computer Vision, 2018
912018
Learning hierarchical attention for weakly-supervised chest X-ray abnormality localization and diagnosis
X Ouyang, S Karanam, Z Wu, T Chen, J Huo, XS Zhou, Q Wang, ...
IEEE transactions on medical imaging 40 (10), 2698-2710, 2020
872020
Depthsynth: Real-time realistic synthetic data generation from cad models for 2.5 d recognition
B Planche, Z Wu, K Ma, S Sun, S Kluckner, O Lehmann, T Chen, A Hutter, ...
2017 International conference on 3d vision (3DV), 1-10, 2017
872017
Ensemble attention distillation for privacy-preserving federated learning
X Gong, A Sharma, S Karanam, Z Wu, T Chen, D Doermann, A Innanje
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
842021
Keeping a Pan-Tilt-Zoom Camera Calibrated
Z Wu, R Radke
IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (8), 1994-2007, 2013
832013
Multi-Shot Human Re-Identification Using Adaptive Fisher Discriminant Analysis
Y Li, Z Wu, S Karanam, RJ Radke
British Machine Vision Conference, 2015
792015
From the Lab to the Real World: Re-Identification in an Airport Camera Network
O Camps, M Gou, T Hebble, S Karanam, O Lehmann, Y Li, R Radke, ...
IEEE Transactions on Circuits and Systems for Video Technology, 2016
702016
Spatio-temporal representation factorization for video-based person re-identification
A Aich, M Zheng, S Karanam, T Chen, AK Roy-Chowdhury, Z Wu
Proceedings of the IEEE/CVF international conference on computer vision, 152-162, 2021
692021
End-to-end learning of keypoint detector and descriptor for pose invariant 3D matching
G Georgakis, S Karanam, Z Wu, J Ernst, J Kosecka
Computer Vision and Pattern Recognition (CVPR), 2018 IEEE Conference on, 2018
642018
A comprehensive evaluation and benchmark for person re-identification: Features, metrics, and datasets
S Karanam, M Gou, Z Wu, A Rates-Borras, O Camps, RJ Radke
arXiv:1605.09653, 2016
64*2016
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20