Gu Wang

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 3 papers; trusts 338 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 108 citations into it; #9,833 of 21,575 by trust here, #10,905 by citations
• Aerospace Engineering — 72 citations into it; #2,796 of 6,421 by trust here, #2,315 by citations
• Control and Systems Engineering — 27 citations into it; #3,833 of 8,257 by trust here, #2,213 by citations
• 3D Vision & Pose — 15 citations into it
• Artificial Intelligence — 13 citations into it
• Industrial and Manufacturing Engineering — 8 citations into it
• Human-Computer Interaction — 5 citations into it

Whom Gu Wang trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Eric Brachmann
4. David G. Lowe
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Andrew Zisserman
8. Diederik P. Kingma
9. Yoshua Bengio
10. Yann LeCun

Who trusts Gu Wang overall

1. Bowen Wen
2. Yisheng He
3. Fabian Manhardt
4. Chen Song
5. Yann Labb'e
6. Yana Hasson
7. Sergey Zakharov
8. Zhigang Li
9. Wei Yang
10. Xingyu Liu

Papers from Gu Wang's perspective

Ordered by how strongly the researchers Gu Wang 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. ImageNet: A large-scale hierarchical image database
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

• DeepIM: Deep Iterative Matching for 6D Pose Estimation (2018) — 791 citations
• CDPN: Coordinates-Based Disentangled Pose Network for Real-Time RGB-Based 6-DoF Object Pose Estimation (2019) — 492 citations
• GDRNPP: A Geometry-Guided and Fully Learning-Based Object Pose Estimator (2021) — 303 citations