Qing Liu
Qing Liu
Johns Hopkins Unversity
Verified email at jhu.edu - Homepage
Title
Cited by
Cited by
Year
Semantic-Aware Knowledge Preservation for Zero-Shot Sketch-Based Image Retrieval
Q Liu, L Xie, H Wang, A Yuille
Proceedings of the IEEE International Conference on Computer Vision, 3662-3671, 2019
282019
Compositional convolutional neural networks: A deep architecture with innate robustness to partial occlusion
A Kortylewski, J He, Q Liu, AL Yuille
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
262020
Combining compositional models and deep networks for robust object classification under occlusion
A Kortylewski, Q Liu, H Wang, Z Zhang, A Yuille
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020
25*2020
Compositional convolutional neural networks: A robust and interpretable model for object recognition under occlusion
A Kortylewski, Q Liu, A Wang, Y Sun, A Yuille
International Journal of Computer Vision 129 (3), 736-760, 2021
112021
Incremental few-shot meta-learning via indirect discriminant alignment
Q Liu, O Majumder, A Achille, A Ravichandran, R Bhotika, S Soatto
European Conference on Computer Vision, 685-701, 2020
9*2020
Seeing the meaning: Vision meets semantics in solving pictorial analogy problems
H Lu, Q Liu, N Ichien, AL Yuille, KJ Holyoak
Proceedings of the Annual Conference of the Cognitive Science Society, 2019
62019
Semantic part detection via matching: Learning to generalize to novel viewpoints from limited training data
Y Bai, Q Liu, L Xie, W Qiu, Y Zheng, AL Yuille
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
52019
Incremental Meta-Learning via Indirect Discriminant Alignment
Q Liu, O Majumder, A Achille, A Ravichandran, R Bhotika, S Soatto
arXiv preprint arXiv:2002.04162, 2020
32020
Unleashing the potential of cnns for interpretable few-shot learning
B Deng, Q Liu, S Qiao, A Yuille
22018
Visual analogy: Deep learning versus compositional models
N Ichien, Q Liu, S Fu, KJ Holyoak, A Yuille, H Lu
arXiv preprint arXiv:2105.07065, 2021
12021
CGPart: A Part Segmentation Dataset Based on 3D Computer Graphics Models
Q Liu, A Kortylewski, Z Zhang, Z Li, M Guo, Q Liu, X Yuan, J Mu, W Qiu, ...
arXiv preprint arXiv:2103.14098, 2021
12021
Compositional Generative Networks and Robustness to Perceptible Image Changes
A Kortylewski, J He, Q Liu, C Cosgrove, C Yang, AL Yuille
2021 55th Annual Conference on Information Sciences and Systems (CISS), 1-8, 2021
12021
Weakly Supervised Instance Segmentation for Videos with Temporal Mask Consistency
Q Liu, V Ramanathan, D Mahajan, A Yuille, Z Yang
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
12021
Localizing Occluders with Compositional Convolutional Networks
A Kortylewski, Q Liu, H Wang, Z Zhang, A Yuille
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
2019
Few-shot Learning by Exploiting Visual Concepts within CNNs
B Deng, Q Liu, S Qiao, A Yuille
arXiv preprint arXiv:1711.08277, 2017
2017
Incremental Few-Shot Meta-Learning via Indirect Discriminant Alignment-Supplementary Material
Q Liu, O Majumder, A Achille, A Ravichandran, R Bhotika, S Soatto
Using Causal Inference to Estimate What-if Outcomes for Targeting Treatments
Q Liu, K Henry, Y Xu, S Saria
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Articles 1–17