Pingping Zhang

Computer Vision and Pattern Recognition · IEEE International Conference on Computer Vision · 2016–2017

A researcher in the Science corpus: 4 papers; trusts 745 researchers and is trusted by 75 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 159 citations into it; #3,206 of 21,575 by trust here, #4,001 by citations
• Sensory Systems — 30 citations into it
• Artificial Intelligence — 29 citations into it
• Cognitive Neuroscience — 26 citations into it; #3,099 of 10,852 by trust here, #3,702 by citations
• Model Architectures — 13 citations into it
• Evaluation & Benchmarks — 7 citations into it
• Media Technology — 7 citations into it; #2,246 of 3,621 by trust here, #1,282 by citations
• Optimization & Training — 7 citations into it

Whom Pingping Zhang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Ross B. Girshick
6. Andrew Zisserman
7. Yoshua Bengio
8. Huchuan Lu
9. Yann LeCun
10. Ilya Sutskever

Who trusts Pingping Zhang overall

1. Deng-Ping Fan
2. Wenguan Wang
3. Jiangjiang Liu
4. Huchuan Lu
5. Zhe Wu
6. Ting Zhao
7. Tiantian Wang
8. Nian Liu
9. Youwei Pang
10. Xuebin Qin

Papers from Pingping Zhang's perspective

Ordered by how strongly the researchers Pingping Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Saliency Detection with Recurrent Fully Convolutional Networks (2016) — 532 citations
• Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection (2017) — 790 citations
• A Stagewise Refinement Model for Detecting Salient Objects in Images (2017) — 416 citations
• Learning Uncertain Convolutional Features for Accurate Saliency Detection (2017) — 447 citations