Eric Ng

Computer Vision and Pattern Recognition · with Ebrahimi · 2019

A researcher in the Science corpus: 2 papers; trusts 410 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 102 citations into it; #21,423 of 21,575 by trust here, #9,187 by citations
• Generative Models — 44 citations into it; #1,952 of 1,956 by trust here, #1,150 by citations
• Media Technology — 16 citations into it
• Artificial Intelligence — 15 citations into it
• Computer Graphics and Computer-Aided Design — 14 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Model Architectures — 10 citations into it
• Optimization & Training — 6 citations into it

Whom Eric Ng trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Kaiming He
4. Alex Krizhevsky
5. Karen Simonyan
6. Yoshua Bengio
7. Yann LeCun
8. Ross B. Girshick
9. Andrew Zisserman
10. Christian Szegedy

Who trusts Eric Ng overall

1. Junke Wang
2. Yuqing Ma
3. Zongyu Guo
4. Yanhong Zeng
5. Håkon Hukkelås
6. Weihao Xia
7. Jie Yang
8. André Peter Kelm
9. Tao Yu
10. Chen Gao

Papers from Eric Ng's perspective

Ordered by how strongly the researchers Eric Ng 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning (2019) — 788 citations
• EdgeConnect: Structure Guided Image Inpainting using Edge Prediction (2019) — 532 citations