Zhenhua Feng

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 5 papers; trusts 565 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 255 citations into it; #9,098 of 21,575 by trust here, #6,146 by citations
• Artificial Intelligence — 34 citations into it; #14,703 of 35,345 by trust here, #25,040 by citations
• Aerospace Engineering — 20 citations into it
• Electrical and Electronic Engineering — 18 citations into it
• Global and Planetary Change — 13 citations into it

Whom Zhenhua Feng trusts overall

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

1. Martin Danelljan
2. Ross B. Girshick
3. Kaiming He
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Andrea Vedaldi
7. Diederik P. Kingma
8. Yann LeCun
9. Yoshua Bengio
10. Karen Simonyan

Who trusts Zhenhua Feng overall

1. Hui Li
2. Yotam Nitzan
3. Zhipeng Zhang
4. Goutam Bhat
5. Xiaojun Wu
6. Bjoern Browatzki
7. Martin Danelljan
8. Xinyao Wang
9. Ke Sun
10. Amit H. Bermano

Papers from Zhenhua Feng's perspective

Ordered by how strongly the researchers Zhenhua Feng 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Object Tracking (2018) — 364 citations
• Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks (2017) — 464 citations
• The Sixth Visual Object Tracking VOT2018 Challenge Results (2018) — 797 citations
• The Eighth Visual Object Tracking VOT2020 Challenge Results (2020) — 345 citations
• The Seventh Visual Object Tracking VOT2019 Challenge Results (2019) — 486 citations