I am currently a senior research scientist and manager at Snapchat working on research projects about computer vision and deep learning. I have finished my Ph.D. in Computer Science at UC Berkeley in 2015, advised by Professor Trevor Darrell.
My research focuses on computer vision and machine learning. In particular, my Ph.D. thesis is about fine-grained categorization. Before coming to US, I graduated from Tsinghua University with a B.S. in Computer Science in June 2010, working with Professor Jie Tang. I have spent summers at Facebook AI Research, working with Dr. Lubomir Bourdev.
We are hiring at Snapchat, please email me if you are interested in a research scientist or research engineer position.
Multi-view to Novel view: Synthesizing novel views from Self-Learned Confidence
Shao-Hua Sun, Minyoung Huh, Yuan-Hong Liao, Ning Zhang, Joseph J. Lim.
European Conference on Computer Vision (ECCV), 2018
Visual Attention Model for Name Tagging in Multimodal Social Media
Di Lu, Leonardo Neves, Vitor Carvalho, Ning Zhang, Heng Ji.
56th Annual Meeting of the Association for Computational Linguistics (ACL), 2018
AutoScaler: Scale-Attention Networks for Visual Correspondence
Shenlong Wang, Linjie Luo, Ning Zhang, Li-Jia Li.
British Machine Vision Conference (BMVC), 2017(Oral)
Deep Reinforcement Learning-Based Image Captioning With Embedding Reward
Zhou Ren, Xiaoyu Wang, Ning Zhang, Xutao Lv, Li-Jia Li.
Computer Vision and Pattern Recognition (CVPR), 2017(Oral)
Fine-grained pose prediction, normalization, and recognition
Ning Zhang, Evan Shelhamer, Yang Gao, Trevor Darrell.
International Conference on Learning Representations (ICLR) workshop, 2016
Compact Bilinear Pooling
Yang Gao, Oscar Beijbom, Ning Zhang, Trevor Darrell.
Computer Vision and Pattern Recognition (CVPR), 2016
Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues
Ning Zhang, Manohar Paluri, Yaniv Tagiman, Rob Fergus, Lubomir Bourdev.
Computer Vision and Pattern Recognition (CVPR), 2015
Do Convnets Learn Correspondence?
Jonathan Long, Ning Zhang, Trevor Darrell.
Neural Information Processing Systems Foundation (NIPS), 2014
Part-based R-CNNs for Fine-grained Category Detection.
Ning Zhang, Jeff Donahue, Ross Girshick, Trevor Darrell.
European Conference on Computer Vision (ECCV), 2014 (Oral)
PANDA: Pose Aligned Networks for Deep Attribute Modeling.
Ning Zhang, Manohar Paluri, Marc'Aurelio Ranzato, Trevor Darrell, Lubomir Bourdev.
Computer Vision and Pattern Recognition (CVPR), 2014 (Oral)
Open-vocabulary Object Retrieval
Sergio Guadarrama, Erik Rodner, Kate Saenko, Ning Zhang, Ryan Farrell, Jeff Donahue, Trevor Darrell.
Robotics Science and Systems (RSS), 2014
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, Trevor Darrell.
International Conference on Machine Learning (ICML), 2014
Deformable Part Descriptors for Fine-grained Recognition and Attribute Prediction
Ning Zhang, Ryan Farrell, Forrest Iandola, Trevor Darrell.
International Conference on Computer Vision (ICCV), 2013
Pose Pooling Kernels for Sub-category Recognition
Ning Zhang, Ryan Farrell, Trevor Darrell.
Computer Vision and Pattern Recognition (CVPR), 2012
Birdlets: Subordinate Categorization Using Volumetric Primitives and Pose-Normalized Appearance.
Ryan Farrell, Om Oza, Ning Zhang, Vlad I. Morariu, Trevor Darrell, Larry S. Davis.
International Conference on Computer Vision (ICCV), 2011 (Oral)
Head of Graduate Student Instructor, UC Berkeley (Spring 2014)
CS 189: Introduction to Machine Learning
Graduate Student Instructor, UC Berkeley (Fall 2013)
CS 188: Introduction to Aritificial Intelligence