Ning Zhang

Affiliations:
  • Snapchat Inc., Venice, CA, USA
  • University of California, Berkeley, CA, USA (PhD 2015)


According to our database1, Ning Zhang authored at least 13 papers between 2011 and 2016.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2016
Compact Bilinear Pooling.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Visual Representations for Fine-grained Categorization.
PhD thesis, 2015

Fine-grained pose prediction, normalization, and recognition.
CoRR, 2015

Beyond frontal faces: Improving Person Recognition using multiple cues.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014
Deep Domain Confusion: Maximizing for Domain Invariance.
CoRR, 2014

Open-vocabulary Object Retrieval.
Proceedings of the Robotics: Science and Systems X, 2014

Do Convnets Learn Correspondence?
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition.
Proceedings of the 31th International Conference on Machine Learning, 2014

Part-Based R-CNNs for Fine-Grained Category Detection.
Proceedings of the Computer Vision - ECCV 2014, 2014

PANDA: Pose Aligned Networks for Deep Attribute Modeling.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction.
Proceedings of the IEEE International Conference on Computer Vision, 2013

2012
Pose pooling kernels for sub-category recognition.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011
Birdlets: Subordinate categorization using volumetric primitives and pose-normalized appearance.
Proceedings of the IEEE International Conference on Computer Vision, 2011


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