Rui Wang

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 430 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 140 citations into it; #6,244 of 21,575 by trust here, #9,187 by citations
• Aerospace Engineering — 98 citations into it; #984 of 6,421 by trust here, #1,784 by citations
• Geology — 19 citations into it
• Media Technology — 17 citations into it
• Artificial Intelligence — 16 citations into it
• Electrical and Electronic Engineering — 12 citations into it
• Evaluation & Benchmarks — 12 citations into it
• Robotics & Control — 11 citations into it

Whom Rui Wang trusts overall

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

1. Jakob J. Engel
2. Daniel Cremers
3. Raul Mur-Artal
4. Jürgen Sturm
5. Andrew J. Davison
6. Christian Kerl
7. Andreas Geiger
8. Kaiming He
9. Georg S. W. Klein
10. Diederik P. Kingma

Who trusts Rui Wang overall

1. Nan Yang
2. Carlos Campos
3. Jiawei Mo
4. César Debeunne
5. Zachary Teed
6. Jamie Watson
7. Andrea Pilzer
8. Lukas von Stumberg
9. Daniel Cremers
10. Richard Elvira

Papers from Rui Wang's perspective

Ordered by how strongly the researchers Rui Wang 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. ImageNet Large Scale Visual Recognition Challenge
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. Attention is All you Need (Neural Information Processing Systems)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry (2020) — 464 citations
• Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras (2017) — 374 citations
• Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry (2018) — 356 citations
• LDSO: Direct Sparse Odometry with Loop Closure (2018) — 319 citations