Zhibin Hong

Computer Vision and Pattern Recognition · 2013–2019

A researcher in the Science corpus: 4 papers; trusts 299 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 98 citations into it; #9,728 of 21,575 by trust here, #7,092 by citations
• Artificial Intelligence — 27 citations into it
• Aerospace Engineering — 10 citations into it; #2,738 of 6,421 by trust here, #2,026 by citations
• Electrical and Electronic Engineering — 6 citations into it; #5,358 of 16,539 by trust here, #7,175 by citations

Whom Zhibin Hong trusts overall

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

1. David G. Lowe
2. Kaiming He
3. Yurii E. Nesterov
4. Geoffrey E. Hinton
5. Navneet Dalal
6. Ross B. Girshick
7. Alex Krizhevsky
8. Andrew Zisserman
9. Yoshua Bengio
10. Pedro F. Felzenszwalb

Who trusts Zhibin Hong overall

1. Hyeonseob Nam
2. Matthias Mueller
3. Ran Tao
4. Luca Bertinetto
5. Yu Zhang
6. Yibing Song
7. Martin Danelljan
8. Sangdoo Yun
9. Lianghua Huang
10. Zhenhua Feng

Papers from Zhibin Hong's perspective

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

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

Their papers

• MUlti-Store Tracker (MUSTer): A cognitive psychology inspired approach to object tracking (2015) — 639 citations
• ACFNet: Attentional Class Feature Network for Semantic Segmentation (2019) — 301 citations
• Multi-graph-view Learning for Graph Classification (2014) — 52 citations
• Tracking via Robust Multi-task Multi-view Joint Sparse Representation (2013) — 162 citations